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Top 15 FinTech Case Studies [A Detailed Exploration] [2024]

In the dynamic realm of financial technology—often abbreviated as FinTech—groundbreaking innovations have revolutionized how we interact with money, democratizing access to myriad financial services. No longer confined to traditional banking and financial institutions, today’s consumers can easily invest, transact, and manage their finances at their fingertips. Through a deep dive into the top five FinTech case studies, this article seeks to illuminate the transformative power of financial technology. From trailblazing start-ups to industry disruptors, we will unravel how these companies have reshaped the financial landscape, offering invaluable lessons for consumers and future FinTech leaders.

Top 15 FinTech case studies [A Detailed Exploration] [2024]

Case study 1: square – democratizing payment processing.

Launched in 2009 by Twitter co-founder Jack Dorsey, Square sought to fill a gaping hole in the financial services market—accessible payment processing for small businesses. In an industry overshadowed by high costs and complexity, Square introduced a game-changing point-of-sale (POS) system, using a tiny card reader that could be plugged into a smartphone.

Key Challenges

1. High Costs: The financial burden of traditional payment systems made it difficult for small businesses to participate, affecting their growth and market reach.

2. Complexity: Legacy systems were cumbersome, requiring hefty upfront investments in specialized hardware and software, with a steep learning curve for users.

3. Limited Accessibility: Many small businesses had to resort to cash-only operations, losing potential customers who preferred card payments.

Related: Important FinTech KPIs Explained

Strategies Implemented

1. User-Friendly Hardware: Square’s portable card reader was revolutionary. Easy to use and set up, it integrated seamlessly with smartphones.

2. Transparent Pricing: A flat-rate fee structure eliminates hidden costs, making budgeting more predictable for businesses.

3. Integrated Business Solutions: Square went beyond payment processing to offer additional services such as inventory management, analytics, and loans.

Results Achieved

1. Market Penetration: As of 2023, Square boasted over 4 million sellers using its platform, solidifying its market position.

2. Revenue Growth: Square achieved significant financial gains, reporting $4.68 billion in revenue in Q2 2021—a 143% year-over-year increase.

3. Product Diversification: Expanding its ecosystem, Square now offers an array of services from payroll to cryptocurrency trading through its Cash App.

Key Learnings

1. Simplicity is Key: Square’s user-centric design proved that simplifying complex processes can open new markets and encourage adoption.

2. Holistic Ecosystems: Offering integrated services can foster customer loyalty and increase lifetime value.

3. Transparency Builds Trust: A clear, straightforward fee structure can differentiate a FinTech solution in a market known for its opaqueness.

4. Accessibility: Providing easy-to-use and affordable services can empower smaller businesses, contributing to broader economic inclusion.

Related: Benefits of Green FinTech for Businesses

Case Study 2: Robinhood – Democratizing Investment

Founded in 2013, Robinhood burst onto the financial scene with a disruptive promise—commission-free trading. Unlike traditional brokerage firms that charged a fee for every trade, Robinhood allowed users to buy and sell stocks at no direct cost. The platform’s user-friendly interface and sleek design made it particularly appealing to millennials and Gen Z, demographics often underrepresented in the investment world.

1. High Commissions: Traditional brokerages often had fee structures that discouraged individuals, especially younger investors, from participating in the stock market.

2. Complex User Interfaces: Many existing trading platforms featured clunky, complicated interfaces that were intimidating for novice investors.

3. Limited Access: Entry-level investors often felt the investment landscape was an exclusive club beyond their financial and technical reach.

1. Commission-Free Trading: Robinhood’s flagship offering eliminated the financial barriers that commissions presented, inviting a new cohort of individual investors into the market.

2. User-Friendly Design: A sleek, intuitive interface made stock trading less intimidating, broadening the platform’s appeal.

3. Educational Resources: Robinhood provides educational content to help novice investors understand market dynamics, equipping them for more informed trading.

1. Market Disruption: Robinhood’s model has pressured traditional brokerage firms to rethink their fee structures, with several following suit by offering commission-free trades.

2. User Growth: As of 2023, Robinhood has amassed over 23.2 million users, a testament to its market penetration.

3. Public Scrutiny: Despite its success, Robinhood has not been without controversy, especially regarding its revenue model and lack of transparency. These issues have sparked widespread debate about ethical practices in fintech.

1. User-Centricity Drives Adoption: Robinhood’s easy-to-use platform illustrates that reducing friction encourages higher user engagement and diversifies the investor base.

2. Transparency is Crucial: The controversies surrounding Robinhood serve as a cautionary tale about the importance of transparent business practices in building and maintaining consumer trust.

3. Disruption Spurs Industry Change: Robinhood’s entry forced a reevaluation of longstanding industry norms, underscoring the influence a disruptive FinTech company can wield.

Related: How to Get an Internship in the FinTech Sector?

Case Study 3: Stripe – Simplifying Online Payments

Founded in 2010 by Irish entrepreneurs Patrick and John Collison, Stripe set out to solve a significant problem—simplifying online payments. During that time, businesses looking to accept payments online had to navigate a complex labyrinth of banking relationships, security protocols, and regulatory compliance. Stripe introduced a straightforward solution—APIs that allow businesses to handle online payments, subscriptions, and various other financial transactions with ease.

1. Complex Setup: Traditional online payment methods often require cumbersome integration and extensive documentation.

2. Security Concerns: Handling financial transactions online raised issues about data safety and compliance with financial regulations.

3. Limited Flexibility: Most pre-existing payment solutions were not adaptable to specific business needs, particularly for start-ups and SMEs.

1. Simple APIs: Stripe’s suite of APIs allowed businesses to integrate payment gateways effortlessly, removing barriers to entry for online commerce.

2. Enhanced Security: Stripe implemented robust security measures, including tokenization and SSL encryption, to protect transaction data.

3. Customization: Stripe’s modular design gave businesses the freedom to tailor the payment experience according to their specific needs.

1. Broad Adoption: Stripe’s intuitive and secure payment solutions have attracted a diverse client base, from start-ups to Fortune 500 companies.

2. Global Reach: As of 2023, Stripe operates in over 46 countries, testifying its global appeal and functionality.

3. Financial Milestone: Stripe’s valuation skyrocketed to $50 billion in 2023, making it one of the most valuable FinTech companies globally.

1. Ease of Use: Stripe’s success proves that a user-friendly, straightforward approach can go a long way in attracting a wide range of customers.

2. Security is Paramount: Handling financial data requires stringent security measures, and Stripe’s focus on secure transactions sets an industry standard.

3. Scalability and Flexibility: Providing a modular, customizable solution allows businesses to scale and adapt, increasing customer satisfaction and retention.

Related: FinTech Skills to Add in Your Resume

Case Study 4: Coinbase – Mainstreaming Cryptocurrency

Founded in 2012, Coinbase set out to make cryptocurrency trading as simple and accessible as using an email account. At the time, the world of cryptocurrency was a wild west of complicated interfaces, murky regulations, and high-risk investments. Coinbase aimed to change this by offering a straightforward, user-friendly platform to buy, sell, and manage digital currencies like Bitcoin, Ethereum, and many others.

1. User Complexity: Before Coinbase, cryptocurrency trading required high technical know-how, making it inaccessible to the average person.

2. Security Risks: The lack of centralized governance in the crypto world led to various security concerns, including hacking and fraud.

3. Regulatory Uncertainty: The absence of clear regulations concerning cryptocurrency created a hesitant environment for both users and investors.

1. User-Friendly Interface: Coinbase developed a sleek, easy-to-use platform with a beginner-friendly approach, which allowed users to start trading with just a few clicks.

2. Enhanced Security: The platform incorporated advanced security features such as two-factor authentication (2FA) and cold storage for digital assets to mitigate risks.

3. Educational Content: Coinbase offers guides, tutorials, and other educational resources to help demystify the complex world of cryptocurrency.

1. Mass Adoption: As of 2023, Coinbase had over 150 million verified users, contributing significantly to mainstreaming cryptocurrencies.

2. Initial Public Offering (IPO): Coinbase went public in April 2021 with a valuation of around $86 billion, highlighting its commercial success.

3. Regulatory Challenges: While Coinbase has succeeded in democratizing crypto trading, it continues to face scrutiny and regulatory hurdles, emphasizing the sector’s evolving nature.

1. Accessibility Drives Adoption: Coinbase’s user-friendly design has played a pivotal role in driving mass adoption of cryptocurrencies, illustrating the importance of making complex technologies accessible to everyday users.

2. Security is a Selling Point: In an ecosystem rife with security concerns, robust safety measures can set a platform apart and attract a broader user base.

3. Regulatory Adaptability: The ongoing regulatory challenges highlight the need for adaptability and proactive governance in the fast-evolving cryptocurrency market.

Related: Top FinTech Interview Questions and Answers

Case Study 5: Revolut – All-In-One Financial Platform

Founded in 2015, Revolut started as a foreign currency exchange service, primarily focusing on eliminating outrageous foreign exchange fees. With the broader vision of becoming a financial super-app, Revolut swiftly expanded its services to include digital banking, stock trading, cryptocurrency exchange, and other financial services. This rapid evolution aimed to provide users with an all-encompassing financial solution on a single platform.

1. Fragmented Services: Before Revolut, consumers had to use multiple platforms for various financial needs, leading to a fragmented user experience.

2. High Costs: Traditional financial services, particularly foreign exchange and cross-border payments, often have hefty fees.

3. Slow Adaptation: Conventional banking systems were slow to integrate new financial technologies, leaving a gap in the market for more agile solutions.

1. Unified Platform: Revolut combined various financial services into a single app, offering users a seamless experience and a one-stop solution for their financial needs.

2. Competitive Pricing: By leveraging FinTech efficiencies, Revolut offered competitive rates for services like currency exchange and stock trading.

3. Rapid Innovation: The platform continually rolled out new features, staying ahead of consumer demand and forcing traditional institutions to catch up.

1. User Growth: As of 2023, Revolut has amassed over 30 million retail customers, solidifying its reputation as a financial super-app.

2. Revenue Increase: In 2021, Revolut’s revenues climbed to approximately $765 million, indicating its business model’s viability.

3. Industry Influence: Revolut’s multi-functional capabilities have forced traditional financial institutions to reconsider their offerings, pushing the industry toward integrated, user-friendly solutions.

1. User-Centric Design: Revolut’s success stems from its focus on solving real-world consumer problems with an easy-to-use, integrated platform.

2. Agility Wins: In the fast-paced world of fintech, the ability to innovate and adapt quickly to market needs can be a significant differentiator.

3. Competitive Pricing is Crucial: Financial services have always been a cost-sensitive sector. Offering competitive pricing can draw users away from traditional platforms.

Related: Surprising FinTech Facts and Statistics

Case Study  6 : Chime – Revolutionizing Personal Banking

Essential term: digital banking.

Digital banking represents the digitization of all traditional banking activities, where financial services are delivered predominantly through the internet. This innovation caters to a growing demographic of tech-savvy users seeking efficient and accessible banking solutions.

Founded in 2013, Chime entered the financial market with a bold mission: to redefine personal banking through simplicity, transparency, and customer-centricity. At a time when traditional banks were mired in fee-heavy structures and complex service models, Chime introduced a revolutionary no-fee model complemented by a streamlined digital experience, challenging the status quo of personal banking.

1. Fee-Heavy Structure: Traditional banks heavily relied on various fees, including overdraft and maintenance charges, alienating a significant portion of potential customers, particularly those seeking straightforward banking solutions.

2. Complexity and Inaccessibility: Conventional banking systems were often marred by cumbersome procedures and lacked user-friendly interfaces, making them less appealing, especially to younger, more tech-savvy generations.

3. Customer Service: The traditional banking sector frequently struggled with providing proactive and responsive customer service, creating a gap in customer satisfaction and engagement.

1. No-Fee Model: By eliminating common banking fees such as overdraft fees, Chime positioned itself as a customer-friendly alternative, significantly attracting customers frustrated with traditional banking penalties.

2. User-Friendly App: Chime’s app was designed with user experience at its core, offering an intuitive and accessible platform for everyday banking operations, thereby enhancing overall customer experience.

3. Automatic Savings Tools: Chime innovated with features like automatic savings round-up and early paycheck access, designed to empower customers in their financial management.

1. Expansive Customer Base: Chime successfully captured a broad market segment, particularly resonating with millennials and Gen Z, evidenced by its rapid accumulation of millions of users.

2. Catalyst for Innovation: The company’s growth trajectory and model pressured traditional banks to reassess and innovate their fee structures and service offerings.

3. Valuation Surge: Reflecting its market impact and success, Chime’s valuation experienced a substantial increase, marking its significance in the banking sector.

1. Customer-Centric Approach: Chime’s journey underscores the importance of addressing customer pain points, such as fee structures, and offering a seamless digital banking experience, which can be instrumental in rapid user base growth.

2. Innovation in Features: The introduction of genuinely helpful financial management tools can significantly differentiate a FinTech company in a competitive market.

3. Disruptive Influence: Chime’s success story illustrates how a digital-first approach can disrupt and challenge traditional banking models, paving the way for new, innovative banking experiences.

Related: Is FinTech Overhyped?

Case Study  7 : LendingClub – Pioneering Peer-to-Peer Lending

Essential term: peer-to-peer (p2p) lending.

Peer-to-Peer (P2P) lending is a method of debt financing that enables individuals to borrow and lend money without using an official financial institution as an intermediary. This model directly connects borrowers and lenders through online platforms.

LendingClub, founded in 2006, emerged as a trailblazer in the lending industry by introducing a novel P2P lending model. This innovative approach offered a substantial departure from the traditional credit system, typically dominated by banks and credit unions, aiming to democratize access to credit.

1. High-Interest Rates: Traditional loans were often synonymous with high-interest rates, rendering them inaccessible or financially burdensome for many borrowers.

2. Limited Access to Credit: Conventional lending mechanisms frequently sidelined individuals with lower credit scores, creating a significant barrier to credit access.

3. Intermediary Costs: The traditional lending process involves numerous intermediaries, leading to additional costs and inefficiencies for borrowers and lenders.

1. Direct Platform: LendingClub’s platform revolutionized lending by directly connecting borrowers with investors, reducing the overall cost of obtaining loans.

2. Risk Assessment Tools: The company employed advanced algorithms for assessing the risk profiles of borrowers, which broadened the spectrum of loan accessibility to include individuals with diverse credit histories.

3. Streamlined Process: LendingClub’s online platform streamlined the loan application and disbursement processes, enhancing transparency and efficiency.

1. Expanded Credit Access: LendingClub significantly widened the avenue for credit, particularly benefiting those with less-than-perfect credit scores.

2. Influencing the Market: The P2P lending model introduced by LendingClub prompted traditional lenders to reconsider their rates and processes in favor of more streamlined, borrower-friendly approaches.

3. Navigating Regulatory Hurdles: The journey of LendingClub highlighted the intricate regulatory challenges of financial innovation, underscoring the importance of adaptive compliance strategies.

1. Efficiency of Direct Connections: Eliminating intermediaries in the lending process can lead to substantial cost reductions and process efficiency improvements.

2. Broadening Credit Accessibility: FinTech can play a pivotal role in democratizing access to financial services by implementing innovative risk assessment methodologies.

3. Importance of Regulatory Compliance: Sustainable innovation in the FinTech sector necessitates a keen awareness and adaptability to the evolving regulatory landscape.

Related: Who is a FinTech CTO?

Case Study  8 : Brex – Reinventing Business Credit for Startups

Essential term: corporate credit cards.

Corporate credit cards are specialized financial tools designed for business use. They offer features like higher credit limits, rewards tailored to business spending, and, often, additional tools for expense management.

Launched in 2017, Brex emerged with a bold vision to transform how startups access and manage credit. In a financial landscape where traditional corporate credit cards posed steep requirements and were often misaligned with the unique needs of burgeoning startups, Brex introduced an innovative solution. Their model focused on the company’s cash balance and spending patterns rather than relying on personal credit histories.

1. Inaccessibility for Startups: Traditional credit systems, with their reliance on extensive credit history, were largely inaccessible to new startups, which typically lacked this background.

2. Rigid Structures: Conventional corporate credit cards were not designed to accommodate rapidly evolving startups’ fluid and dynamic financial needs.

3. Personal Guarantee Requirement: A common stipulation in business credit involves personal guarantees, posing a significant risk for startup founders.

1. No Personal Guarantee: Brex innovated by offering credit cards without needing a personal guarantee, basing creditworthiness on business metrics.

2. Tailored Financial Solutions: Understanding the unique ecosystem of startups, Brex designed its services to be flexible and in tune with their evolving needs.

3. Technology-Driven Approach: Utilizing advanced algorithms and data analytics, Brex could assess the creditworthiness of startups in a more nuanced and comprehensive manner.

1. Breaking Barriers: Brex made corporate credit more accessible to startups, removing traditional barriers.

2. Market Disruption: By tailoring its product, Brex pressures traditional financial institutions to innovate and rethink its credit card offerings.

3. Rapid Growth: Brex’s unique approach led to rapid adoption within the startup community, significantly growing its customer base and market presence.

1. Adapting to Market Needs: Brex’s success underscores the importance of understanding and adapting to the specific needs of your target market.

2. Innovative Credit Assessment: Leveraging technology for credit assessment can open new avenues and democratize access to financial products.

3 Risk and Reward: The move to eliminate personal guarantees, while riskier, positioned Brex as a game-changer, highlighting the balance between risk and innovation in FinTech.

Related: Is FinTech a Dying Career Industry?

Case Study  9 : SoFi – Transforming Personal Finance

Essential term: financial services platform.

A financial services platform offers a range of financial products and services, such as loans, investment options, and banking services, through a unified digital interface.

SoFi, short for Social Finance, Inc., was founded in 2011 to revolutionize personal finance. Initially focused on student loan refinancing, SoFi quickly expanded its offerings to include a broad spectrum of financial services, including personal loans, mortgages, insurance, investment products, and a cash management account. This expansion was driven by a vision to provide a one-stop financial solution for consumers, particularly catering to the needs of early-career professionals.

1. Fragmented Financial Services: Consumers often had to navigate multiple platforms and institutions to manage their various financial needs, leading to a disjointed financial experience.

2. Student Loan Debt: Many graduates needed more flexible and affordable refinancing options with student debt escalating.

3. Accessibility and Education: A significant segment of the population lacked access to comprehensive financial services and the knowledge to navigate them effectively.

1. Diverse Financial Products: SoFi expanded its product range beyond student loan refinancing to include a suite of financial services, offering more holistic financial solutions.

2. Tech-Driven Approach: Utilizing technology, SoFi provided streamlined, user-friendly experiences across its platform, simplifying the process of managing personal finances.

3. Financial Education and Advice: SoFi offered educational resources and personalized financial advice, positioning itself as a partner in its customers’ financial journey.

1. Expanding Consumer Base: SoFi succeeded in attracting a broad customer base, especially among young professionals looking for integrated financial services.

2. Innovation in Personal Finance: The company’s expansion into various financial services positioned it as a leader in innovative personal finance solutions.

3. Brand Recognition and Trust: With its comprehensive approach and focus on customer education, SoFi built a strong brand reputation and trust among its users.

1. Integrated Services Appeal: Offering a broad array of financial services through a single platform can attract customers seeking a unified financial management experience.

2. Leveraging Technology for Ease: Using technology to simplify and streamline financial services is key to enhancing customer experience and satisfaction.

3. Empowering Through Education: Providing users with financial education and advice can foster long-term customer relationships and trust.

Related: FinTech vs Investment Banking

Case Study  10 : Apple Pay – Redefining Digital Payments

Essential term: mobile payment system.

A mobile payment system allows consumers to make payments for goods and services using mobile devices, typically through apps or integrated digital wallets.

Launched in 2014, Apple Pay marked Apple Inc.’s foray into the digital payment landscape. It was introduced with the aim of transforming how consumers perform transactions, focusing on enhancing the convenience, security, and speed of payments. Apple Pay allows users to make payments using their Apple devices, employing Near Field Communication (NFC) technology. This move was a strategic step in leveraging the widespread use of smartphones for financial transactions.

1. Security Concerns: The rising incidences of data breaches and fraud in digital payments made consumers skeptical about the security of mobile payment systems.

2. User Adoption: Convincing consumers to shift from traditional payment methods like cash and cards to a digital platform requires overcoming ingrained habits and perceptions.

3. Merchant Acceptance: For widespread adoption, a large number of merchants needed to accept and support Apple Pay.

1. Enhanced Security Features: Apple Pay uses a combination of device-specific numbers and unique transaction codes, ensuring that card numbers are not stored on devices or servers, thereby enhancing transaction security.

2. Seamless Integration: Apple Pay was designed to work seamlessly with existing Apple devices, offering an intuitive and convenient user experience.

3. Extensive Partnership with Banks and Retailers: Apple forged partnerships with numerous banks, credit card companies, and retailers to ensure widespread acceptance of Apple Pay.

1. Widespread Adoption: Apple Pay quickly gained a significant user base, with millions of transactions processed shortly after its launch.

2. Market Leadership: Apple Pay became one of the leading mobile payment solutions globally, setting a standard in the digital payment industry.

3. Influence on Payment Behaviors: The introduction of Apple Pay substantially accelerated the shift towards contactless payments and mobile wallets.

1. Trust Through Security: The emphasis on security can be a major driving force in user adoption of new financial technologies.

2. Integration and Convenience: A system that integrates seamlessly with users’ daily lives and provides tangible convenience can successfully change long-standing consumer habits.

3. Strategic Partnerships: Building a network of partnerships is key to the widespread acceptance and success of a new payment system.

Related: FinTech Failure Examples

Case Study  11 : Ant Group (Formerly Ant Financial) – A Global Digital Payment and Lifestyle Platform

Ant Group, founded in 2014 as a subsidiary of Alibaba, created Alipay, a revolutionary digital payment platform. Alipay quickly became one of the largest digital wallets globally, offering services like fund transfers, bill payments, and lifestyle solutions.

1. Market Fragmentation: The digital payment market was crowded with various regional players competing for dominance.

2. Regulatory Scrutiny: Ant Group faced strict regulations around data security, anti-money laundering, and financial stability.

3. Trust Issues: Getting users to trust an entirely digital platform for handling their finances was challenging.

1. Diverse Service Ecosystem: Alipay expanded beyond payments to offer travel booking, wealth management, insurance, and more.

2. Partnerships: Collaborated with global financial institutions to widen its user base.

3. Data Security: Implemented advanced data security measures to ensure transactions were safe.

1. Global Reach: Alipay grew to over 1 billion users globally, with significant market penetration outside China.

2. Diversification: The platform diversified to include financial services, creating a comprehensive lifestyle app.

3. Valuation Growth: Ant Group achieved a multi-billion-dollar valuation, underscoring its industry influence.

1. Ecosystem Strategy: Providing a complete and integrated range of services can help to boost user engagement and foster loyalty.

2. Regulatory Agility: Navigating regulatory challenges requires proactive compliance and collaboration with authorities.

3. Global Partnerships: Strategic alliances can significantly enhance market reach.

Related: How to Value a FinTech Company?

Case Study  12 : Nubank – Revolutionizing Banking in Latin America

Nubank, established in 2013, is a prominent digital bank globally and a top FinTech in Latin America. It started with credit cards before expanding into other banking services, aiming to offer user-friendly and accessible banking to underbanked populations.

1. Financial Inclusion: A large portion of the population in Latin America was unbanked or underbanked.

2. Trust in Financial Systems: Many people lack trust in traditional financial institutions due to high fees and poor customer service.

3. Market Complexity: The regional market posed challenges due to regulatory differences across Latin American countries.

1. No-Fee Model: Offered a no-fee credit card that appealed to customers tired of hidden fees.

2. Customer-Centric Design: Developed an intuitive mobile app to simplify banking transactions.

3. Market Expansion: Adopted a localized approach for market expansion across multiple countries.

1. Rapid Growth: Nubank has garnered over 40 million customers, growing swiftly beyond Brazil.

2. Innovation Leader: Recognized as an industry innovator for driving digital banking adoption.

3. Investment Magnet: By drawing significant investments, Nubank has emerged as one of the most valuable FinTech companies worldwide.

1. Localized Strategy: Customizing services based on regional market needs is vital for rapid growth.

2. Customer Trust: Transparent, no-fee models can build customer trust and drive adoption.

3. Simplified UX: A user-friendly interface simplifies banking for previously underserved customers.

Related: FinTech vs Finance: Key Differences

Case Study  13 : Klarna – Transforming E-Commerce Payments

Founded in 2005, Klarna is a pioneer in BNPL, offering an alternative to credit cards. Its seamless integration with online merchants and easy-to-understand payment plans attracted millions of users.

1. Consumer Trust: Convincing consumers to trust a new payment method required overcoming skepticism.

2. Merchant Acceptance: Onboarding merchants and integrating the solution with existing payment systems was challenging.

3. Regulatory Concerns: BNPL faced scrutiny around potential overspending and consumer debt.

1. Simple User Experience: Developed a clear, intuitive checkout process, reducing payment friction.

2. Merchant Partnerships: Partnered with thousands of merchants, integrating seamlessly into e-commerce platforms.

3. Consumer Education: Educated consumers on responsible spending and minimizing debt risk.

1. Merchant Network: Klarna is now partnered with over 250,000 retailers worldwide.

2. Market Adoption: Millions of consumers use Klarna for seamless e-commerce transactions.

3. Industry Influence: Klarna’s BNPL model inspired similar solutions across the FinTech industry.

1. Simple Integration: Seamless merchant integration can accelerate solution adoption.

2. Consumer Responsibility: Educating consumers on spending habits minimizes debt risk.

3. New Payment Model: BNPL offers a viable alternative to traditional credit systems, transforming e-commerce payments.

Related: Top FinTech Terms Defined

Case Study  14 : Plaid – Connecting Financial Data Seamlessly

Founded in 2013, Plaid aimed to streamline how people connect their financial data to various apps. It bridges the gap between users’ bank accounts and financial apps like budgeting tools, payment platforms, and lending services.

1. Data Security: Accessing sensitive financial data requires robust security measures.

2. Standardization Issues: Banks had different protocols, making establishing a consistent connection difficult.

3. Regulatory Compliance: Navigating data protection laws across regions posed a significant challenge.

1. Secure APIs: Developed secure APIs to facilitate safe and standardized access to financial data.

2. Bank Partnerships: Collaborated with major financial institutions to ensure consistent data access.

3. Developer Focus: Provided developers with comprehensive tools and documentation for easy integration.

1. Developer Adoption: Plaid’s APIs became the backbone for thousands of financial apps.

2. Market Penetration: The platform now connects to thousands of financial institutions worldwide.

3. M&A Success: Plaid’s impact attracted significant acquisitions and partnerships within the FinTech ecosystem.

1. Data Security Focus: Prioritizing data security builds user trust and drives adoption.

2. Standardization: Developing standardized protocols for data access is crucial in fragmented markets.

3. Ecosystem Collaboration: Building partnerships with financial institutions is vital for seamless integration.

Related: Can FinTech Replace Banks?

Case Study  15 : Adyen – Unifying Global Payments

Established in 2006, Adyen is a global payment company offering merchants a single, unified platform for all their payment needs. It aimed to streamline payment acceptance by simplifying the process across various channels, payment methods, and regions.

1. Regional Fragmentation: Payment methods and regulations varied significantly by region.

2. Omnichannel Complexity: Offering consistent payment experiences across multiple channels was difficult.

3. Merchant Onboarding: Merchants struggled with complex onboarding processes and technical integrations.

1. Unified Platform: Created a single platform where merchants could accept payments across regions and channels.

2. Regional Compliance: Ensured the platform met regulatory requirements for each region.

3. Omnichannel Focus: Merchants can now offer uniform payment experiences across various channels including online, in-store, and mobile, thanks to the enabled technology.

1. Global Reach: Adyen became a preferred payment platform for merchants worldwide.

2. Unified Experience: Both merchants and consumers benefited from the platform’s unified approach as it simplified the payment process for both parties.

3. Merchant Growth: Adyen merchants have reported enhanced customer satisfaction and increased conversion rates.

1. Unified Approach: A unified approach simplifies payment acceptance across channels and regions.

2. Regulatory Compliance: Adapting to local regulatory requirements is essential to ensure smooth cross-border operations.

3. Omnichannel Presence: Maintaining consistency across all payment channels can improve the customer experience and drive business growth.

Related: Pros and Cons of FinTech Career

These stories of globally renowned FinTech trailblazers offer invaluable insights, providing a must-read blueprint for anyone looking to make their mark in this rapidly evolving industry.

1. Square shows that focusing on user needs, especially in underserved markets, can drive innovation and market share.

2. Robinhood serves as both an inspiration and a cautionary tale, advocating for democratization while emphasizing the importance of ethical practices.

3. Stripe proves that simplifying complex processes through customizable, user-friendly solutions can redefine industries.

4. Coinbase highlights the transformative potential of making new financial instruments like cryptocurrency accessible while reminding us of regulatory challenges.

5. Revolut sets the bar high with its user-centric, all-in-one platform, emphasizing the need for agility and competitive pricing in the sector.

The key to FinTech success lies in simplicity, agility, user focus, and ethical considerations. These case studies serve as guiding lights for future innovation, emphasizing that technological superiority must be balanced with customer needs and ethical responsibilities.

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Case Study | Banking and Financial Services

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How we brought resiliency to our leading FinTech client’s operations, transforming their business processes and driving efficiencies to enhance the overall customer experience.

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Supporting Rapid Growth Without Additional Operating Cost

As a large financial services company and one of the first peer-to-peer lenders, our client’s business had seen significant growth - including the recent acquisition of another bank.

There was a pressing need to optimize and streamline systems to integrate the businesses, but the client’s systems and processes weren’t set up for the transition. They faced high operating costs and inefficiencies as a result, which were hurting the customer experience.

Our client needed to unify and harmonize their business processes while leveraging AI and automation to transform the customer experience.

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Paytm Case Study: The Journey of India's Leading FinTech Company

Devashish Shrivastava

Paytm is India's one of the biggest fintech startups founded in August 2010 by Vijay Shekhar Sharma. The startup offers versatile instalments, e-wallet, and business stages. Even though it began as an energizing stage in 2010, Paytm has changed its plan of action to become a commercial centre and a virtual bank model. It is likewise one of the pioneers of the cashback plan of action.

Paytm has changed itself into an Indian mammoth managing versatile instalments, banking administrations, commercial centre, Paytm gold, energize and charge installments, Paytm wallet and many other provisions which serve around 100 million enlisted clients.

The areas served by Paytm are India, Canada, and Japan, it is also accessible in 11 Indian dialects . It offers online use-cases as versatile energizes, service charge installments, travel, motion pictures, and occasions appointments. In-store instalments at markets, leafy foods shops, cafés, stopping, tolls, drug stores and instructive establishments can be accessed through the Paytm QR code.

One 97 Communications, the parent company of Paytm, is all set to raise its capital target of over ₹16,600 crores ($2.2 billion) through an IPO that it had filed earlier in July 2021. Paytm is seeking to raise $25 billion to $30 billion valuation post this IPO.

According to the organization, more than 7 million traders crosswise over India utilize its QR code to acknowledge instalments straightforwardly into their bank account. The organization uses commercials and pays a special substance to produce income. Let's look at this detailed case study on Paytm to know more about its growth and future plans.

Paytm - Latest News Origin of Paytm Business Model of Paytm Business Growth of Paytm Expected Future Growth of Paytm Why was Paytm Removed from Google Play Store?

Paytm - Latest News

1st November 2021 - The much-awaited Paytm IPO was launched with a price band of ₹ ₹2,080-2,150 per share.

13th October 2021 - Paytm users can now store Aadhaar, driving license, vehicle RC, insurance via Digilocker. Digilocker Mini App on Paytm offers access to these documents to users even when they're offline or in a low connectivity zone.

8th October 2021 - Paytm is looking forward to bringing in sovereign wealth funds as anchor investors in the company's pre-IPO placement.

5th October 2021 - Switzerland-based insurance giant, Swiss RE might join Paytm's insurance business' board.

3rd October 2021 - Paytm has acquired 100% stakes in CreditMate, a Mumbai-based digital lending startup.

Origin of Paytm

The saga and the emergence of Paytm are discussed in this section of the case study of Paytm. It was established in August 2010 with underlying speculation of $2 million by its originator Vijay Shekhar Sharma in Noida, an area nearby India's capital New Delhi .

It began as a prepaid portable and DTH energize stage, and later included information card, postpaid versatile and landline charge installments in 2013. By January 2014, the organization propelled the Paytm pocketbook, and the Indian Railways and Uber included it as an installment option.

It propelled into web-based business with online arrangements and transport ticketing.

In 2015, it disclosed more use-cases like instruction expenses, metro energizes power, gas, and water charge installments. Paytm likewise began driving the installment passage for the Indian Railways.

In 2016, Paytm propelled motion pictures, occasions, and entertainment meccas ticketing just as flight ticket appointments and Paytm QR. Later that year, it propelled rail bookings and gift vouchers . Paytm's enrolled client base developed from 11.8 million in August 2014 to 104 million in August 2015. Its movement business crossed $500 million in annualized GMV run rate, booking two million tickets for each month.

In 2017, Paytm became India's first installment application to traverse 100 million application downloads. That year, it propelled Paytm Gold, an item that enables clients to purchase as meagre as ₹1 of unadulterated gold on the web . It additionally propelled the Paytm Payments Bank and 'Inbox', and informing stage with in-talk installments among other products.

By 2018, it began enabling dealers to acknowledge Paytm UPI and card installments straightforwardly into their financial balances at 0% charge. It likewise propelled the 'Paytm for Business' application, enabling traders to follow their installments and everyday settlements instantly. This drove Paytm's shopper base to more than 7 million by March 2018.

The organization propelled two new riches—Paytm Gold Savings Plan and Gold Gifting—to rearrange long haul savings. It propelled into diversion and speculations, and stripe alongside AGTech to dispatch the stage of a transportable game Gamepind, and putting in Paytm cash with a venture of ₹9 large integers to bring venture and riches as board items for Indians. In May 2019, Paytm joined forces with Citibank to dispatch credit cards .

Business Model of Paytm

Paytm or "Payment Through Mobile" is India's biggest installment, trade, and e-wallet undertaking. It began in 2010 and is a brand of the parent organization One97 Communications, established by Vijay Shekhar Sharma. It was propelled as an online portable energize site and proceeded to change its plan of action to a virtual and commercial centre bank model.

The organization stands today as one of India's biggest online portable administrations that incorporates banking administrations, commercial centres, versatile installments, charge installments, and energize. It has so far given administrations to more than 100 million clients.

Paytm's enhancement has built a solid reputation and has turned out to be praiseworthy for some in the online installment industry. One of its increasingly vital accomplishments is in its joint effort with the Chinese web-based business Goliath, Alibaba for immense measures of subsidizing.

Aside from being a pioneer of the cashback plan of action, the organization has been commended for its introduction as a new business able to build huge partnerships in a limited time period.

Clients of Paytm Business

Paytm's core focus is on serving its Indian client base, especially the cell phone clients. Numerous Indian clients saw the computerized world as an opportunity to open a financial balance. Accessing simple online installments missed the mark, and clients wound up with only poor experience. Paytm presented itself as a superior option to deal with such situations.

Paytm Offers

A portion of Paytm's increasingly conspicuous suggestions was reviving the business which was the organization's underlying administration recommendation.

At that point, it proceeded to differentiate and progressed to creating more current administrations from any semblance of Paytm Wallet, E-business vertical to Digital Gold.

These improvements were appreciated in the form of the Chinese mammoth Alibaba's favours. Immense totals of cash were pumped into Paytm by Alibaba, expanding Paytm's speculation potential. Paytm used cricket and TV promotion to capture more clients.

Relationship with Clients

Paytm has a 24*7 client care focus to interface with its clients. Simultaneously, the vast majority of Paytm administrations are self-served in nature and are open through their foundation straightforward.

Paytm's Channel for Business

Paytm utilizes numerous channels to draw in clients. Aside from its very own site which drives clicks, Paytm has shaped associations with numerous customers and seller destinations that support its endeavour. Demonetization in India enabled the organization to succeed altogether and arrive at new clients too. Disconnected advertising is likewise a piece of their client procurement process.

Distinct Advantages

The RBI (Reserve Bank of India) permit fills in as Paytm's fundamental asset. It should be explicit to Paytm. Different assets like the plan/programming society make it simpler for lower-pay Indians to use Paytm.

Paytm, being an innovation stage, dangers perils, for example, security and misrepresentation which is the reason it needs to take viable measures in ensuring its buyer's cash by improving its security. It is likewise rolling out new improvements inside its foundation to draw in new clients and access their computerized wallets.

Partners of Paytm

Paytm accomplices with the banks that give it installment excursions into the financial framework just as escrow administrations. It works together with a heap of associations that accumulate bills and installments from its customers for its administration.

Structure of Costing

Paytm serves numerous clients which is the motivation behind why it is so cost-driven. The vast majority of its costs are identified with its foundation and client obtaining. It's a typical cost-shared by numerous organizations over the reality where client securing cost is significant.

The cash utilized in this procedure is higher than the income it makes in its underlying buys. Most of its financial limit is to put resources into sloping up of its security and stay away from the danger of misrepresentation, particularly when it needs to deal with more than 65 million clients in its foundation. It incorporates a framework that empowers clients to avoid any tax evasion hazard .

Revenue Model of Paytm

The Paytm revenue models come in two structures. Paytm makes commissions from the client exchanges through their utilization of its foundation. Escrow Accounts are the accounts from where it creates their income. Inferable from the non-appearance of its hidden capital, it offers clients no intrigue. Starting in 2018 Paytm has aggregated 3314.8 crore INR in income.

Paytm Wallet

Paytm wallet is one of Paytm's best benefits that structures a connection between the bank and the retailers. This semi-shut wallet empowers you to take care of your tabs, pay for your tickets, or pay anyone concerned.

Paytm wallet separated from its profit, as approved by the RBI, has the advantage of accepting enthusiasm for a purchaser store, much the same as some other Payment Gateways .

When you store a specific measure of cash in your Paytm wallet, it will at that point set aside that cash in another bank from which it will win enthusiasm eventually.

It is the Paytm wallet's fundamental capacity. For instance, suppose you make an installment of Rs. 1000  to a merchant and the vendor makes 10 exchanges to increase Rs. 10,000. If the installment of that sum is made through the Paytm wallet, the Paytm wallet will take a portion of about 1% of the aggregate sum. So the merchant will get around Rs. 9715.

Mobile Recharge Business

Since its origin in 2010, Paytm's underlying intention was to give online portable energizing administrations. Its capacity to create income was constantly shortsighted. Paytm's administration guidelines are as praiseworthy and proficient as those of other telecom specialist co-ops running from Vodafone to Telecom.

The administrations are without shortcomings and give solace to their clients. As of now, Paytm increases a commission of 2-3% per energize. It is because Paytm, attributable to its support to its client to keep reviving through its foundation, has more grounded power in dealing than different merchants. That is the reason the commission it obtains is so high. This commission from its revive administration fills in as its income.

These administrations have supported the organization essentially in extending its base and thus, developing exponentially. When the client is fulfilled by the administration or item, he makes an arrival to a similar undertaking in this manner. This way Paytm does client maintenance and produces more traffic . Paytm has used this methodology to further its potential benefit and keeps on reaping positive results.

Paytm Digital Gold Paytm Digital Gold

Inferable from its organization with MMTC-PAMP, the outstanding gold purifier, Paytm has propelled "Computerized Gold". This model enables clients to sell, purchase, or store gold in an advanced stage. Presently, clients need to pay at a rate just to get their gold conveyed to their families.

Paytm is very much aware of how much gold is put as a resource in India and is completely arranged to develop from this chance. The organization has made eminent arrangements to urge its clients to get their own Gold Bank Accounts individually. This record separated from empowering clients to purchase their gold will likewise furnish clients with simple access to other Paytm administrations.

In February 2017, Paytm propelled its Paytm Mall application which enables purchasers to shop from 1.4 lakh enrolled sellers. Paytm Mall is a B2C model enlivened by the model of China's biggest B2C retail stage, TMall. For 1.4 lakh merchants enlisted, items need to go through Paytm-guaranteed stockrooms and channels to guarantee buyer trust.

Paytm Mall has set up 17 satisfaction focuses crosswise over India and joined forces with 40+ messengers. Paytm Mall raised $200 million from Alibaba Cluster and SAIF Partners in March 2018. In May 2018, it posted losses of roughly Rs 1,800 crore with an income of Rs 774 crore for money related to the year 2018. Moreover, the piece of the pie in Paytm Mall dropped to 3% in 2018 from 5.6% in 2017.

Business Growth of Paytm

Advanced installments organization Paytm has professed to arrive at gross exchange esteem (GTV) of over $50 billion, while checking 5.5 billion exchanges in FY19. The Delhi NCR-based organization credited this development to the rising appropriation of Paytm over numerous utilization cases, for example, retail installments, expenses, utility installments, travel booking , excitement, games among others. It has as of late propelled membership-based prizes program (Paytm First) to aid development alongside expanding the client maintenance.

Discussing the feasible arrangements, senior VP of Paytm, Deepak Abbot stated, "We are centred around creating tech-driven arrangements, incorporated client lifecycle the board, upgrading the client experience and growing to Tier 4-5 urban communities. We are certain to accomplish 12 Bn exchanges before the part of the bargain year." Before a month ago, the Ministry Of Electronics and Information Technology (MeitY) had solicited Paytm to help its objective of encouraging 40 Bn advanced exchanges in FY20.

The organization shared designs to incorporate man-made brainpower in its model and achieve 2x development this year. Paytm professed to possess half piece of the installment entryway industry in India, with 400 Mn month to month exchanges on the stage.

Established by Vijay Shekhar Sharma in 2010, Paytm furnishes various new companies and huge organizations with arrangements running from a shareable PaytmQR code to profound coordination.

It empowers clients to process computerized installments through any favoured installment mode including credit and check cards, net banking, Paytm wallet, and UPI (bound together installment interface). Paytm had likewise propelled its very own installments bank in 2017.

Paytm Payments Bank is versatile first keep money with zero charges on every online exchange, (for example, IMPS, NEFT, RTGS) and no base equalization prerequisite. For investment accounts, the bank right now offers a loan cost of 4% per annum.

Expected Future Growth of Paytm

Computerized installments organization Paytm said it is looking to dramatically increase its exchange volume to 12 billion by part of the arrangement, from 5.5 billion out of 2018-19.

Paytm checked 2.5 billion exchanges in 2017-18. Paytm said it accomplished gross exchange esteem (GTV) of $50 billion out of 2018-19, as contrasted and $25 billion every year prior. GTV is the estimation of all-out exchanges done on the stage.

"This expansion is a consequence of the fast development in the reception of Paytm's computerized installments arrangements crosswise over on the web and disconnected for different use cases including retail installments, charges, utility installments, travel booking, amusement, games and that's only the tip of the iceberg,"

The organization said in an announcement. Its membership-based program Paytm First was propelled in March has pulled into equal parts a million supporters, the organization added.

Paytm has 350 million enrolled clients starting on 5 June, an organization authority said. Paytm offers a variety of installment alternatives that incorporate installment through portable wallets, just like ongoing installment framework Unified Payments Interface (UPI) and web banking.

The organization has been centred around structure instruments for dealers to streamline their everyday business needs. This has brought about enormous dealers obtaining who are very much furnished with innovation to acknowledge all installment modes (cards, wallet, and UPI). Paytm now intends to concentrate on embracing computerized reasoning and improving the UI .

Why was Paytm Removed from Google Play Store?

Paytm India app was removed from Google Play Store because it violated Google guidelines. While other apps like Paytm for Business, Paytm mall , Paytm Money, and a few more were still available. But after a few hours of being taken down, the Paytm app was back on Google Play Store.

#Paytm out of Google Play Store. Google: We don’t allow online casinos/support any unregulated gambling apps that facilitate sports betting. It includes if app leads consumers to an external website that allows them to participate in paid tournaments to win real money/cash prizes pic.twitter.com/poeZzXw5nA — CNBC-TV18 (@CNBCTV18Live) September 18, 2020

“We have these policies to protect users from potential harm. When an app violates these policies, we notify the developer of the violation and remove the app from Google Play until the developer brings the app into compliance. And in the case where there are repeated policy violations, we may take more serious action which may include terminating Google Play Developer accounts. Our policies are applied and enforced on all developers consistently,” Google Added.

Is Paytm a fintech company?

Yes, Paytm is India's leading and one of the most valued fintech startups founded by Vijay Shekar Sharma in 2010.

What are the areas served by Paytm?

Paytm is a leading fintech startup that not only operates in India but it also serves Canada and Japan.

When was Paytm established?

Paytm was founded in 2010 by Vijay Shekar Sharma.

What is Paytm and how does it work?

Paytm is a leading financial service and bill payments app that offers financial solutions to its customers, offline merchants and online platforms. All you need to do is open the Paytm app on your phone, click on 'Pay', and select 'QR code'. Scan the QR code of the receiver and enter the amount to be paid. The money will be transferred in a few seconds.

How much does Vijay Shekhar Sharma own in Paytm?

Vijay Shekhar Sharma currently owns 14.61% of the company.

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FINTECH EXPLAINED

Links to Companies Analyzed in Fintech Explained

Adyen ’s market multiples of comparable companies

Innovations by Alipay    in payments

Amazon’s path into financial services

Ant Group and Tencent’s multi-sided platforms

Apple’s partnering with incumbents

Bitcoin’s solution to the double-spend problem and price volatility

Credit Karma’s $7 billion multi-sided platform

The DAO Hack questions the immutability of blockchains

Ethereum’s vision and dominance of DeFi

Facebook’s troubles with regulators

Rise and fall of the FTX cryptoexchange

Funding Circle’s financial ratios and performance in online lending

Goldman Sachs’ entry into consumer banking with Marcus

Google’s struggle to find product-market fit

JPMorgan’s value drivers and valuation in traditional banking

Kickstarter’s mission to bring creative projects to life

Lendified’s use of artificial intelligence (AI)

LendingClub’s marketplace lending platform

LUNA’s unstable stablecoin TerraUSD

MakerDAO and Curve Finance’s use-cases

Moven’s   personal finance apps

Nubank building Latin America’s sixth largest bank

Innovations by   Octopus in payments

Paytm’s business model and monetization strategy

R3 Corda’s Permission DLT for regulated financial services

Ripple XRP’s search for a use-case

Robinhood’s commission-free trading for retail

  Sensibill ’s   personal finance apps

SoFi’s evolution from P2P lender to full-service bank

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Vanguard’s move into robo-advice

Innovations by Vodafone's  M-Pesa  in payments

Wealthfront’s sophisticated, low-cost financial advice

Robo-advisor Wealthsimple’s seed-stage pitch to angel investors

Wise Financial’s pain point and market opportunity in payments

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FinTech Case Studies

Uc berkeley faculty member gregory la blanc stresses that it’s all about the data.

UC Berkeley Haas Global Access Program (BHGAP) and BHGAP Innovation Program faculty member Gregory La Blanc recently hosted a Zoom meeting where he gave viewers a sneak peek into his FinTech class.

Check out the highlights from his talk below and watch the full video!

Citibank was the 300th largest bank in the United States. How do you go from the 300th largest bank in the United States to the largest credit card issuer in the entire world?

With machine learning, with data science, with analytics.

They saw that every single bank in the country is using the same scoring model: If your credit score is above this cutoff, you get a loan; if you're below this cutoff, you don't get a loan.

They said that there must be a more fine-grained model—to find the people who are rejected and see if a few of them might turn out to be good customers. They lent a whole bunch of money to people whom the other model said don't lend money to.

There were a lot of defaults. A lot of people didn't repay their loans. There was a reason why they were generally considered bad credits.

However, after seven or eight months, they were able to determine that a small percentage of them were good credits. So after seven or eight months, they ended the experiment. They cancelled the credit cards of most of the customers.

And what were they left with? A couple of good customers and an amazing proprietary database. They had some training data that they could then feed through an algorithm, and that algorithm would say, here is what makes these good customers similar to one another, and here is what makes bad customers similar to one other. So if you want to find good credit risks, go look for people who look like this.

That's how they were able to scale and grow and become the largest credit card issuer in the world.

This is what's given rise to lots of new startups in the borrowing and lending space. All of them are using different types of machine learning models to identify good credit risks.

In my class , we also hear from people who work at peer-to-peer lending companies. What they really should be called are algorithmic lenders. They use data that other banks don't use. They're going beyond the traditional data sets and finding signals of credit-worthiness that the traditional banks don't look at.

One thing they could look at is your location data.

If a bank is tracking my location, they know something about me. They know that I went to work. Then I spent a couple of hours at LinkedIn headquarters. Then I head over to Google headquarters and then I hit Facebook headquarters for a couple hours in the afternoon.

Banks can use this information to revise my credit score up or down.

If we drill down into location data, we can figure out whom this person is meeting with. What room are they in inside the Facebook headquarters? What building are they in? Who are they sitting next to at that meeting?

If you don't have a unique, proprietary data source, you don't have a sustainable competitive advantage and you'll ultimately be commodified.

There's a company called Tala , and it works in countries like Kenya where people have no documentation: no banking history, no income history, no employment history, no housing history. And yet they can still lend money to these people because they download the Tala app, and the app scours their phone for data.

Kai-Fu Lee , a famous Chinese venture capitalist, visited Haas about two years ago, and he talked about a FinTech startup that he'd invested in. This startup used alternative data to evaluate credit. And he said that one of the most important signals that they had discovered of credit-worthiness was how people managed their battery life. You can track this because you have access to their phone data. People who let their batteries go all the way down to zero are bad credit risks compared to those who are topping off their batteries at 20 or 30 percent.

Even though it's absolutely essential and critical that every company use analytics, machine learning and data science, that alone cannot provide you with a competitive advantage. At the end of the day, that is a commodity. Anybody can learn how to do this, and anybody can hire away anybody else who knows how to do this.

Your competitive advantage has to come from your data—not from what you do with the data or how you use the data. I would argue that if you don't have a unique, proprietary data source, you don't have a sustainable competitive advantage and you'll ultimately be commodified.

Watch the entire video:

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Targeting an untapped fintech market worth trillions: A conversation with Arta Finance’s Caesar Sengupta

As the eight cofounders of US- and Singapore-based Arta Finance got to know one another during their years together at Google, they recognized a massive market gap for investment services aimed at people like themselves: successful professionals who were doing well, but not well enough to access top-tier financial services. With a total addressable market in the trillions, they decided to launch a fintech start-up offering these elite services at scale, using a digital platform powered by AI. The venture quickly attracted prominent investors and venture capital (VC) funding in excess of $92 million, is already doing business in the United States, and will begin operating in Singapore by early 2024. In this episode of The Venture , Caesar Sengupta, CEO of Arta Finance, sat down with McKinsey’s Tomas Laboutka to discuss Arta’s mission to automate public-market investing and provide access to alternative assets by offering clients the services of a digital private bank and family office.

An edited transcript of the podcast follows. For more conversations on venture building, subscribe to the series on Apple Podcasts or Spotify .

Podcast transcript

Tomas Laboutka: Hi, Caesar. Welcome to The Venture. Great to have you.

Caesar Sengupta: Thanks so much for having me on. It’s wonderful to talk to you.

Tomas Laboutka: Caesar, you’ve had a really successful career at Google. For 15 years, you led Google Pay in India, and you were at the helm for the development of the Chromebooks. You could have kept going, but you decided to jump ship and go build Arta Finance. What’s the story behind this?

Caesar Sengupta: Great question, and I like how you’ve put it. When you find an opportunity that’s even bigger than what you’re working on, I think all things lead toward going and doing it. Arta, in many ways, originated out of some of our team’s experiences at Google. I have eight cofounders; we’re a rather weird company. And among the eight cofounders, we spent eight to 15 years working together and became friends.

As friends talk about finances and money, we realized there was a massive market gap for serving professionals who are doing well and will eventually have a much greater net worth. They are not quite at the $20 million to $25 million level, where a private bank would offer them great service, or at an even higher level where they would have their own family office.

These people were not being served, and we felt that need ourselves. And as we spoke to others, we realized there’s a huge global opportunity. We estimate several hundred million people worth trillions in the total addressable market (TAM) in need of a service like this, where we offer private banking or digital family office services to them at scale, using technology and AI.

Once we saw this opportunity, we felt like the timing was right, given where we were with technology, AI, and our careers. It was not quite in line with what Google does—Google is not a wealth manager—so we decided the best way to do this would be to start something up on our own, with a lot of support from friends and others at Google and elsewhere.

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Tomas Laboutka: What does Arta actually do?

Caesar Sengupta: If you think about a private bank, or a wealth manager, it helps you grow and protect your money. What Arta does is help you grow your assets through investments in public markets. We’ve essentially automated all kinds of public-market investing, ranging from very simple robo-advisers all the way to very sophisticated quant strategies you can personalize by industry. But if all you want to do is invest in a direct index fund in the S&P 500 and use tax-loss harvesting, we’ll let you do that, too.

A lot of people are only invested in public markets. But we think many professionals—just like the ultrarich—should be invested in alternative assets, like private equity, private credit, and private real estate ventures. We give people access to these investments, but at much lower amounts. Instead of the millions you’d have to normally invest, you can start with $25,000, or $100,000 in some cases. It makes these investments much more approachable.

We also offer structured products that are timed investments, so you don’t have to understand the complexities of derivatives, calls, and puts. We also offer tax-advantaged investing, structured through permanent life insurance policies, and set up trusts and estates as well. Essentially, we offer a full value proposition you would expect from a family office or a private bank. We offer that to our members and users via a digital platform, with experts and others providing support wherever needed.

Tomas Laboutka: You’re talking digitally enabled wealth management. There have been robo-advisers and the like for ten to 15 years. What’s the unique value proposition you bring to the table? And what role does AI play?

Caesar Sengupta: As you mentioned, robo-advisers have been around for the last ten years or so. They took a very simple concept of taking balanced portfolios that were rebalanced on a regular basis, and used technology to scale it. What we’ve done is brought it a decade or two into the future. Essentially, we’ve automated all kinds of public-market investments, and also given people access to alternative assets, but at much lower ticket sizes.

In many ways, we are doing what a private bank does, but using technology to scale those services. The way we think about it is, for all those people who started using robo-advisers ten years back, Arta is where you graduate to. Robo-advisers served you well. But as you start thinking about your financial future, and start thinking about scaling up, Arta is where you would come for a full-fledged digital private bank or digital family office.

We use AI in a couple of different ways. We started two years ago, before generative AI came around, so it was mainly machine learning. If you think about a bunch of these very sophisticated quant investment funds, we apply machine learning to some of those technologies and techniques. We can now offer these at an individualized level starting at $25,000.

With generative AI, the potential is so exciting, and the world is just opening up. We’re doing a bunch of work using large language models to enable thematic investing. Today, for example, if you wanted to invest in a particular theme you were excited about, you’d need a fairly sophisticated investment manager to set it up for you, or find an appropriate hedge fund.

But what if you could just type a theme into a system, which then generated assets to fit that theme? You could invest your money, the system would keep an eye on it for you, and all of this would be done with AI. We’re just starting to scratch the surface of generative AI, and I’m super excited about what it can do in the future.

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Tomas Laboutka: That is really fascinating. What are the capabilities you looked for in your cofounders and early employees? What gives you the right to not just play here, but win against the incumbents, against the other start-ups, or a competitor that might be thinking of entering this market?

Caesar Sengupta: When you’re choosing cofounders, there are a few things. First, it’s kind of like a marriage. And in this case, it’s an eight-way marriage. So you need to know your cofounders and believe they are the kind of people you want to spend the next couple of decades working with, deep in the trenches. But a lot of us have worked together for a very long time. About six of us started ChromeOS, and then we started Google Pay. We’ve had a lot of history building products together.

So the first part is the history, the chemistry, and the time you spent working together. The second part is about having the right skill set. In this case, we could see the problem, which was one we faced ourselves. And we could see what the solution could be: using technology. But to build it out, we needed three key skill sets.

First, you need people who can build deep tech, especially AI, at scale. Our CTO, Zelidrag Hornung, ran engineering for Google Pay, and before that, he ran ChromeOS. One of our engineering leaders, another cofounder, was an engineering manager for Gmail, and built and grew Gmail from tens of millions of users to billions of users. These are deep, deep tech people who know how to build and scale, and the team has expanded.

Second, you need people from deep finance. And there are some people on the founding team who came from deep within finance. Our CIO, Chirag Yagnik, has run algorithmic hedge funds. Our insurance business is led by another similar stalwart from the insurance industry, Samita Malik, who spent 20 years building insurance businesses.

The third critical function is driving growth. That requires people who can take these complicated financial tools and jargon and help people understand what this is all about, engage with users, and drive growth. This group includes a lot of the folks who built Google Pay and drove growth globally from zero to hundreds of millions of users. We’ve put together a team with these three skill sets of deep tech, deep finance, and growth drivers, and I think this combination is going to be very effective in creating a scalable platform.

The opportunity here is not to take users away from anyone, because this is a largely untapped market. Most private banks are not able to access, tackle, or cater to investors with a few hundred thousand to $10 million in net worth, profitably. Most consumer banks don’t know how to reach this market, so there’s a completely open space here, which needs a fairly sophisticated product. But you need these three things to build the market and grow the space for everyone.

Tomas Laboutka: How do you get the right resources in terms of funding? Many companies we see building ventures from scratch carry fairly strong balance sheets, and are able to fund start-ups. How are you actually thinking about resources from that perspective?

Caesar Sengupta: There’s one advantage of having a bunch of older people start a company, which is they’re slightly further along in their careers, both in terms of net worth, but also networks. Those two make a big difference. Initially, when we started, we funded ourselves and we knew we had enough funds for a team of about 50 people for about a year, which for most start-ups is actually a pretty amazing luxury.

But as we started talking to people at Google, and this includes Eric Schmidt, the previous CEO, Sundar Pichai, the current CEO, and partners we worked with for many years, two things happened.

First, they all said, “This problem resonates with us. We wish we had this in our lives ten or 20 years back when we were in our 30s and really hitting our stride.” Secondly, they said, “We would love to see this happen and be a part of this journey.” So we ended up getting a huge number of angel investors who came in to support us and help us grow, and we now have 140 of them.

As angel investors were coming in, we started talking to some of the VC funds we’ve worked with in the past and they ended up leading our seed round. After the seed round, we realized there were a number of partners who wanted to engage with us.

We ended up doing a quick follow-on Series A and raised about $92 million. One reason for that was, obviously, the fact we wanted these people on the journey with us. But secondly, when you’re building a wealth management product, you don’t want your users to—even for a moment—think you’re not going to be in the game. We wanted to make sure our users knew we were in this for the long run.

So we raised a lot more and maybe took a little bit more dilution than we otherwise would have. But our goal here is to build a generational company, not maximize the valuation for any of us. We want to see this product thrive. Obviously, we’ll make money doing it, but we feel the opportunity to create a fintech company starting with wealth management is immense.

Tomas Laboutka: I’m curious, how are you thinking about scaling? The industry you’re trying to revolutionize is a heavily licensed and regulated one, where every country has its own rules and regulations. How are you thinking about that versus other competitive solutions, when they see your traction?

Caesar Sengupta: First of all, just a quick point on the competition. As I said, this is a largely untapped market. We see the opportunity as largely greenfield, being able to serve this particular audience, professionals with hundreds of thousands to $5 million, $10 million, or $15 million. We think there’s a massive opportunity here, so we’re very focused on that aspect.

In terms of how we plan to grow from here, we have a B2C effort in the United States, which is direct-to-consumer and focused on a couple of segments. We think our direct engagements will work incredibly well with young professionals in tech, consulting, and finance—the 30-somethings and 40-somethings. We also just received approval to operate in Singapore, so we will be able to open up there sometime early in 2024.

In those markets, we will be going directly to the professionals. But we’re a very ecosystem-friendly and partner-friendly company, and we’re having some great conversations with very large banks and financial institutions around the world, where we will offer private banking as a service. It’s like software as a service (SaaS), but with private banking instead, which partners and banks in other countries will market under their own brand.

One bank in Australia wants to offer not just our technology and user experience, but all of Arta’s products, options, and features. They want to package it together in a box and instantly upgrade their wealth management offering to be competitive with the world’s best banks. We think that’s a pretty interesting option. So that’s the next stage of growth for us internationally, where we offer everything as a SaaS in each country.

Our ultimate goal within the next year is getting to a point where, within a matter of weeks, a bank can offer a new wealth management service in their country and focus on that segment very, very quickly. They handle the regulatory piece and client relationships, while we offer everything else as a service.

Tomas Laboutka: So there’s the B2C play, which is a big market in the United States. You’re getting licensed in Singapore. But you’re also tapping into a second market, which is B2B in a sense, with wealth management as a service. When you bring the whole suite of solutions, including the products in a box, then any partner ultimately unlocks the licensing and regulatory requirement for you, and with that helps you tap into the market. That is a fascinating approach.

Caesar Sengupta: It’s extremely symbiotic. We think partners unlock growth for us, but we also bring something very unique to the partners. This is a playbook we followed over the years at Google. One of my cofounders, Felix Lin, and I manage the partner side of our efforts, just as we did with ChromeOS. Although ChromeOS started as a consumer offering, we then partnered with OEMs and other big distributors to get into education and enterprises, and it created new businesses for everyone.

We did the same thing with Google Pay. We started with a pure peer-to-peer play in India, and today, banks are offering loans on Google Pay, and fixed deposit accounts. You can buy airplane tickets on Google Pay in India, and receive merchant offers through it in the United States. We ended up creating an ecosystem play that made everybody more productive, because we created more opportunities and connections.

This model of starting a B2C, then adding a B2B component on top of it so the overall ecosystem benefits, is something we firmly believe in. It’s part of our core. From day one, when we started talking to our angel investors, this was part of the plan. It just took us two years to get to a point where we could start having conversations with banks and partners in the ecosystem.

Tomas Laboutka: Amazing. This is exactly where you’re answering the question all investors ask: What’s your unique capability? What you’re talking about here is the ultimate triple-A answer from an investor’s perspective. You’re telling them, “Look, I’ve been there and done that multiple times at Google, and I’m doing it with my own venture. And I have the vision, the team, and the resources to make this happen.” It’s really compelling, and I’m keen to see how this story will unfold. Caesar, this has been a really insightful conversation. I’m very much looking forward to having you back on the show a few years from now to hear how the journey is going.

Caesar Sengupta: Absolutely, Tomas, thank you so much.

You have been listening to The Venture . If you like what you’ve heard, subscribe to our show on Apple Podcasts , Spotify , or wherever you listen.

Caesar Sengupta is CEO of Arta Finance. Tomas Laboutka is an associate partner in McKinsey’s Singapore office.

Comments and opinions expressed by interviewees are their own and do not represent or reflect the opinions, policies, or positions of McKinsey & Company or have its endorsement.

McKinsey & Company is not an investment adviser. Nothing in the following materials constitutes or shall be construed as investment advice or a recommendation to proceed or not to proceed with any proposed investment, acquisition, sale, or transaction.

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4 Real-world Fintech case studies by UppLabs

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TABLE OF CONTENTS

• The best UppLabs Fintech practices in detail
• 1. Bank credit collection system
• 2. Rebuilding the legacy banking system
• 3. Improving UX for one of the TOP 4 auditing companies in the US
• 4. Rebuilding multilevel microservices architecture
• Fintech software development by UppLabs

Posted by: UppLabs Team

From projects’ requirements to an effective solution: business goals and tech stack…

In this article, we would like to present to you the real-world Fintech case studies that we implemented, including rebuilding legacy solutions and rebuilding payment systems. Each project required the rebuilding and updating of the old system to the new one, both on the frontend and on the backend sides. Besides, there were other challenges that we are ready to share with you.

Fintech often refers to the combination of finance and technology, which is used to process the business operations and financial services whether it is a software, a service, or a business that implements the technologically progressive ways to make financial processes more efficient by introducing traditional methods.

Over the last 5 years, UppLabs mastered the skills and gained experience in creating reliable, secure, and sophisticated Fintech products . We have strong knowledge of Fintech trends and innovations, constantly learn, visit the best fintech conferences, and have the best team of professional web and mobile developers. Our experience shows that the tech stack you use will determine the possibilities and limitations of your product. 

Below we collected the best Fintech projects developed by UppLabs to show you what practices, technologies, and approaches we used to level up businesses in Fintech.

1. Bank credit collection system 

A credit collection department in one of the famous banks needed a platform for business processes implementation.

Want to find out what bank it was?

Challenges: 

The main challenge was to create a system that would be flexible to the process changes. The team had to review many different options before to choose the right strategy and use the VPN (Virtual Private Network) scheme as a basis for planning.

The solution:  

In order for the solution to be as flexible as possible, in about six months, we designed a system that was based on the VPN model. It could describe this process and complete the necessary tasks and processes.

Technologies:

•  we used Oracle on the backend and ReactJS on the frontend
•  we had a microservice architecture, different parts were related to the integration of banking systems,
•  we used .Net for the backend.

Team : 

There were 2 developers (backend and frontend) responsible for our module, an additional Project Manager, an additional DPA (Database Administrator), and a Head of IT, who was responsible for the whole project.

The task: 

In 2015, we created a project for one of the TOP 10 banks in NY. It was a system that can help to conduct the process of evaluating clients. 

Challenges : 

The main challenge was the rebuild of the old system that was previously written with some bugs. Our team had to identify those bugs and rewrite the legacy product. 

The solution: 

The process of rewriting was very smooth, we didn’t start from scratch, but raised the whole system as it was and added new functionality to fix bugs in their pages. If there were critical bugs, we considered rewriting the module or page using a new approach, and if the bug was not essential, we just fixed the code.

• The team used mainly Java but there was a part of the backend that was written on the . NET that we integrated through the API with the microservice on Java.
• It was a legacy product that was created before using ASP.NET web forms. So, it was converted to a .NET web app and AngularJS. 
• We had a multi-level microservice architecture, where microservices were written using different technologies and approaches. 

We had over 10 Java developers, about 10 .NET developers, a QA team (8 people in Kyiv and 20 people in India), a team of 4 business analysts, a project manager, and 2 team leads. There were 2 more client-side specialists in the United States so that they could communicate with the client on a regular basis and delegate the tasks to other developers.

In 2015-2017 we implemented a project for one famous US auditing company. It demanded rebuilding the system that can conduct the process of evaluating companies and included many different processes. 

The audit documentation was written in the form of a quiz, with the questions based on previous answers. For example, if the company had large financial expenditures, there could appear additional questions and modules for answers. If the company was absolutely transparent and small, then it could go through the fast track module, which significantly reduced the number of additional documents, reviewers, and auditors who had to work with this company and review it.

As we had a certain time limit – a year – to remake the user experience, we couldn’t throw away everything completely. Despite the team we had, we hadn’t enough resources to rewrite everything from scratch in a year. As a result, we decided to separate the modules into the ones that we had to rebuild entirely and the ones that could be re

The most challenging part of this project was the frontend. 

The solution : 

We decided to optimize the backend that remained to be on the .NET, and our team has started rebuilding the system. 

Because of the time restrictions, UppLabs decided to choose:

• the main modules that we can rebuild from scratch, 
• the modules that we will not have time to rebuild, but will be able to finish with the help of redesign or reuse part of the logic. 

Technologies :

• The product’s backend was made on a . NET, the frontend module was made on Knockout and jQuery. It was an old system that already worked, but there was an idea to do an update. 
• The backend included an MS SQL database, and there were a lot of different optimizations to make it all work quickly. 
• The client had an idea to improve User Experience a bit, and UI design in general, so we started rebuilding the system using Knockout and jQuery as well as AngularJS (it was also an old technology). 

We had a team of 15 developers in Ukraine, and 6 QA specialists (one Automation specialist and five manual operators).

In 2017-2018 we worked on a project for a world-known company that provides web analytics services for businesses. We worked in the accounting and billing team, which was directly linked to the financial transactions. 

The solution:  

We used integrations with PayPal, WireTransfer, etc. There was an interesting billing system in general, which was organized on the basis of different approaches. Also, there were subscriptions and additional costs that the company could pay in general. 

Our team used external microservice configurations systems. On the backend, we used Docker-based infrastructure. Everything scaled and deployed automatically to a different number of instances that had load balancers, which raised the number of instances depending on the load. 

The frontend task was to rebuild a system from AngularJS (it was a data-driven project) to ReactJS , and on this basis to raise User Experience and the performance of the website. Our team performed this task successfully.

Technologies : 

• The backend was created using .NET Core and included microservice architecture.
• Each microservice could have its own database, some of them had MySQL, others had more complex solutions.
• The system had a Redshift Database and built OLAP Cubes (databases that we used for integration), other bis data stores for teams. 
• We used Redis on our side, a cache layer with a database for quick access to data.
• Our payment system was connected to Redis and MySQL. To improve the system’s work, we processed operations in Redis, responded to the client, and synchronized Redis with MySQL.  

Team: 

150 developers from different teams that were working on various modules.

As you can see from the examples of our works above, UppLabs proves Fintech expertise by:

• Knowing Fintech regulations by heart
• Using the best security practices for all solutions 
• Providing business advisory in Fintech
• Communicating with financial experts
• Applying the latest technologies for reaching the best results

Our company creates online e-trading platforms that offer real-time solutions with various trading Fintech opportunities, payment systems integrations, money transactions systems, existing banking services maintenance and modernization, and more. 

Our portfolio includes the use of modern architecture that guarantees easy maintenance and easy integration with the best fintech services. 

We give our preferences to such technologies as :

• React Native
• Ruby on Rails

All these technologies are most often used to create web services that require intensive information exchange with users, including the implementation of chats, collaboration systems, social networks, etc. 

From the foregoing, it can be seen that Fintech is going to revolutionize the financial sector in many ways, from increasing the use of payment gateways to providing landings. With much easier account systems and transactions, fintech will also influence the world’s e-commerce industry.

If you’re looking for a Fintech development partner – there is no point in further search!

Check our expertise here . 

UppLabs is a perfect companion to lift you Upp!

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Case Study - A Growing FinTech Company

A growing fintech company, the challenge.

Our client, a growing fintech company, was being acquired by a global financial services company. At the time of our initial conversation with the client, the deal was projected to close within two weeks. After closing, the legacy company needed a strong counsel to take over its legal work. Complicating matters, our client had accumulated a large portfolio of PPP loans as a result of the global pandemic. The PPP loan portfolio was not part of the sale and would remain with the legacy company.

They needed an experienced fintech lawyer to handle the PPP loan portfolio and support the CEO of legacy company. Given the timing of the deal, the lawyer had to be quickly identified, onboarded and brought up to speed. The lawyer also had to be seasoned enough to work directly with the CEO of the legacy company.

The Solution

Our client engaged Interim Legal Talent to help address this challenge because of our experience in the fintech sector and our reputation in the local legal community. We also allowed for the possibility of finding a resource with flexible hours that could potentially convert to a full-time attorney in the indefinite future.

Because we had recently completed a search for another fintech company, we had identified a pool of strong candidates that were available. One of the candidates had 20+ years of experience directly related to the issues that the new servicing company and its CEO would face. She was flexible enough to continue with a long-term contract arrangement with the possibility of converting to a permanent role. After she interviewed with the CEO of the legacy company, they decided to move forward with her. In less than two weeks from our first conversation with our client, they had an interim attorney onboard and producing.

The Results

While this role was initially projected for 20 to 30 hours per week, due to the volume of work, it has required closer to 40 hours. Our interim attorney flexed to meet this additional demand. She is now the sole in-house legal advisor for the legacy company. Because of this, the prior in-house team has been able to focus their efforts on their new responsibilities. In addition to achieving this important objective, our client is saving more than $5,000 per week in legal fees as compared to the cost of having to rely on outside counsel.

By using interim legal talent, you can take the time to carefully consider direct placement hiring options and find an excellent candidate while getting the work done in the meantime.

Need time to figure out the right structure of your legal team before making permanent hires? Take that time and still get the work done with the support of consulting attorneys.

Our client was using an AmLaw 50 firm to handle IT vendor contracts. Recognizing the significant expenses associated with using traditional outside legal counsel, our client sought a more cost-effective approach to meet their legal needs without compromising on quality or expertise.

• Startup of the week

Cred Case Study: The Successful Story of a Fintech Startup

| 4 minutes read

An Indian Fintech Startup, Cred, entered the unicorn club on April 6 th, 2021. CRED had shown a strong footprint and became one of the most successful startups in recent times. Bengaluru, India Based Startup, made its name big, but it has its true story starting from Zero to billions. Although the road was not easy, they made the impossible possible and showed the strength of the Indian startup .

The company was established in 2018 and had a valuation of approximately $2.2 billion. Many other startups like Flipkart and OYO took more than ten years to reach a similar valuation level. 

What is their Business model?

The startup is based on the “Hole and hook model”. It is a common problem that many credit card users don’t pay their credit card bill on time. So the business model of Cred encourages holders to complete payments on time by providing some exclusive rewards including 100% cashback.

The company found the ‘hole’ (flaw) in the credit card payment system and provided a ‘hook’ in rewards. They offer attractive rewards to their customers, which makes their product a brag-worthy proposition.

About the founder

Kunal Shah was also the co-founder of ‘freecharge’. Coming from a Gujarati family and a non-tech background, he is currently the founder of two big tech companies. He was motivated to start CRED after research and understanding the loophole in the overall credit card payment system. He is also the current CEO of the company Cred.

Also Read: Startup Case Study: How Byju’s is Disruption the Indian Edu-tech Sector?

What is their marketing strategy.

The marketing campaign of CRED is universal. They have implemented an aggressive marketing strategy to improve the value of their product. Surabhi Capoor is the brand and product marketing head at CRED.

The company’s marketing department came up with unique advertising ideas that made the brand larger than life. For example, the latest ad featured Kapil Dev (Former Cricketer) acting like a Ranveer Singh that pulled viewers because no one had seen him in this avatar before. Apart from this, during IPL (Indian Premier League), Cred starts to increase its awareness before the beginning of the IPL like the way Vodafone used to do by introducing Zoozoo (character).

Further, the company was marketed through various other celebrities on social media platforms . Meme marketing also worked for the company, and thus the awareness of the brand is on the rise.

What services do they provide?

The company started with just credit card payment services, but now it is expanding its reach in different sectors. The CRED app has more than 60 lakh users, and the number is increasing. 

Listing the services provided in the app.

• It allows you to manage all your credit card payments in one place.
• The app notifies your regular payment details and due dates.
• It offers rewards and cashback for new users.
• The company provides CRED points on the completion of payment, and these points can be used to avail various vouchers and cashback.
• The payment method is hassle-free.
• They have started providing services for rent, loans, and insurance.

How Credible are they?

The company assures total privacy to the customers (claimed by the company). They deal with the valuable financial data of the customers, and they offer complete privacy on it. With such attractive rewards and enhanced security, it is trusted by its users. In just 2 years, they have successfully reached a million consumer base, and their number is ever increasing. 

What is their Mission?

The mission of the company is understood by everyone. They want to improve and enhance the credit card payment system. Despite not making any profit in 2019 and 2020, they have eventually gained the trust of their users. They used the “reward and punishment tendency” effectively to attract and establish the customers base.

CRED & their Vision

CRED’s business model is futuristic. They want to develop themselves in diversified sectors like insurance, rent, shopping, loans, and realty payments. The company also focuses on a futuristic revenue model. 

It aims to generate revenue through merchandising, commission and consulting. They can also use this vast customer base for sales pitching and generate good fortune from it.  

How are they Funded?

CRED is one of those legendary startups that got funding right before its execution. This was made possible by the brilliant execution of the founder Kunal Shah. The company has made a loss of 63.90 crores and 378.89 crores in 2019 and 2020, respectively. Despite these losses, the company is trusted by its investors.

The company has around 28 investors and 7 lead investors. The lead investors are listed below:

•         Dragoneer Investment Group.
•         Tiger Global Management.
•         Sofina.
•         DST Global.
•         Coatue.
•         Falcon Edge Capital.
•         Insight Partners.

The company has raised funding of around $471.3 million from investors. The company’s other investors are Ribbit Capital, Gemini investments, Sequoia Capital India, and Rainmatter Capital.

Who are the Brand Partners?

The company offers different rewards and vouchers for customers. It has successfully bagged many reputed brands as its partner. Some of the esteemed brand partners are:

The story behind their Struggle and Success

Kunal Shah faced a serious dilemma before starting the company. He was offered to become an investing partner in Sequoia Capital of India. But the entrepreneur chose to start a company rather than become an investor. 

The company has also registered itself as an IPL sponsor and has started building some revenue. Despite making losses in the first two years, it has continued to provide valuable services to its users. The company has a futuristic revenue model, and thus it is trusted by its investors.

Born in the family of entrepreneurs and have inherited the same. Started building applications in order to pay for my tuition. Later founded a tech company, marketing agency , and media outlets.

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Revolut Company Case Study: A Fintech Success Story

Revolut Ltd is a fintech company in London, UK and one of the largest startups in Europe, offering a range of banking and payment services through a mobile app and currency cards. Their services include currency exchange, Mobile Banking, Card Payments, Money Remittance, Foreign Exchange, insurance, and more. They favour individuals, freelancers, and small and medium enterprises, and have a global presence across North America, Europe, and Asia-Pacific.

Also Read About: Zerodha Founders

Table of Contents

Brief overview.

Founded – 2015 Founders – Nikolay Storonsky, Vlad Yatsenko Location – London, England, UK Former name – Revolut Operating Status – Active Operating In – Fintech Startup Legal Name – Revolut Ltd. Total Revenue – €375 Million (Wikipedia)

About Revolut Company

Revolut is available in 47 countries, including every country in the EU and EEA. The main origin of the company is in London United Kingdom. Revolut made its debut in India in April 2021, after building on previous successful launches in Singapore and Australia in 2019, as well as in the US and Japan in 2020. Revolut offers financial services designed to simplify and improve the way people manage their money like Revolut Mobile Banking, Card Payments, Money Remittance and Foreign Exchange.

Revolut Mission

Revolut company’s primary mission is to continuously simplify, enhance, and add value to all aspects of financial management, making them significantly more convenient and beneficial for everyone, every single day. To accomplish this mission, Revolut has a workforce that reflects the rich diversity of our customer base.

Revolut Success Story

• The journey of Revolut was started in 2015 by Nikolay Storonsky (CEO and Founder) and Vlad Yatsenko (CTO – Co-Founder) operating in London a fintech incubator.
• After that In 2017 Revolut launched on different platforms like Business, and Revolut Premium, and entered the cryptocurrency market, starting with Crypto Trading in EEA.
• In 2018, Revolut secured $250 million , achieving a post-funding valuation of $1.7 billion, making it unicorn. By December 2018, it obtained a Challenger bank license from the European Central Bank and an Electronic Money Institution license from the Bank of Lithuania for deposits and credits for customers.
• In 2019, Revolut introduced commission-free stock trading with the New York Stock Exchange and Nasdaq and made key hires with traditional banking experience. They made their first expansion into Australia and Singapore. In October 2019, a global partnership with Visa expanded its reach to 3500 new workforce in 24 markets.
• By February 2020, a funding round valued Revolut at £4.2 billion, making it the UK’s most valuable fintech startup . They Launched their app in the USA and Japan and read to 14.5 M users. In March, Revolut launched in the United States, followed by a debut in Japan in August. By the end of the year, the company gained profitability.
• In January 2021, Revolut applied for a UK banking license and later sought a bank charter in the US. In July, Revolut raised $800 M, resulting in a $33 bn valuation, with investments from SoftBank Group and Tiger Global Management. Revolut Company brought about £636 million in revenue in 2021 which was a huge profit for the organization.
• In January 2022, Revolut launched in 10 European countries as a bank. In March Revolut’s public stance against the Russia-Ukraine war, was accompanied by a substantial donation to the Red Cross Ukraine appeal. At that time, it had 18 million global customers and 150 million monthly transactions. In September Revolut UK, witnessed a cyberattack exposing the data of 50,000 customers, prompting regulatory action.
• In January 2023, Revolut shifted its Irish customers to an Irish branch, aiming to compete with traditional banks. Revolut Bank started offering cryptocurrencies in the UK and European Economic Area in 2023. In May the Bank of England poised to reject Revolut’s UK banking license application. By July, Revolut expanded to 30 million customers across 37 countries.
• Revolut app launches in New Zealand with over 26k Kiwis to access free foreign currency exchange ad payments.

Revenue And Profit

In 2021, Revolut experienced substantial financial growth, with revenue surging from £220 million in 2020 to £636 million. The company also achieved a remarkable turnaround in its net income, reporting £26 million in profit compared to a £223 million loss in the same year. Gross margin saw significant improvement, increasing from 33% to 70%. Revenue sources diversified, with cards and interchange contributing 23% £149 million, subscriptions 17% £107 million, and foreign exchange and wealth services representing the majority at 55% £349 million. Shortly after securing around $45.5 million in initial investments from its UK-based parent company, Revolut India announced an upcoming acquisition.

Revolut Challenges

Revolut, amid rapid growth, faced the dual challenge of enhancing user onboarding while combating fraud. The fintech company was confronted with several controversies, including delayed financial filings, EU regulatory breaches, and an aggressive workplace culture. In 2020, despite a 34% revenue increase to £222 million, Revolut posted a £208 million loss. Problems extended to Lithuania, where it holds its EU banking license, with parliamentary investigations and penalties for various issues. A flaw in its US payment system led to a $20 million loss to organized criminal groups. Despite revenue, Revolut reported a record £167 million net loss in 2021. That is affecting the customers in the United States.

Closing Thoughts

Revolut’s journey in the world of fintech touches remarkable growth and notable challenges. From its humble beginnings in London to becoming a global powerhouse in financial services, the company’s mission to simplify and enhance financial management remains at its core. Despite facing regulatory issues, workplace controversies, and financial challenges, Revolut’s commitment to innovation and customer-centric solutions continues to be the future of banking. With millions of users worldwide and a diverse range of services, Revolut UK stands as a transformative potential of fintech, always managing money more convenient and beneficial for everyone.

REFERENCES:

“ Revolut , Revolut reports first full year of profit “ “ Revolut – Story , Revolut: can the chancellor’s fintech favourite fix its image problem? “ “ Revolut onboards 12% more users “

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February 20, 2019

10 Successful FinTech Marketing Case Studies

In an industry that puts a prime on innovation, we’ve seen more creative marketing approaches and ideas coming from the FinTech sector in recent years.

With emerging new technologies setting the pace for many industries, some FinTech companies have gone above and beyond in their marketing strategy, proving that with a little marketing creativity, FinTech companies can be more than just technology focused.  

We’ve picked out ten of the most inspiring marketing examples and case studies from FinTech companies to help you plan your own strategy.  

FinTech Inbound Marketing

In the area of Fintech content marketing , SoFi leads the way in creating a website that acts as a resource centre that offers useful how-to guides and custom calculators. From student loan refinancing to first-time home buying, SoFi’s website offers a lot of useful tools and tips to help people make better financial decisions.

Invisible Marketing

WePay showed everyone the right way to do invisible marketing using emotional triggers when it used a 300-kg ice block of frozen money to get a one-up on its biggest competitor, PayPal.

Wanting to expose PayPal’s tendency to freeze customer accounts, the frozen money ice block, with a link to unfreezeyourmoney.com on it, stunned the crowd.  

With the stunt going viral, it drew 3x more landing page conversions for WePay, increased their sign-ups by up to 225%, and increased their weekly traffic to 300%.

iZettle is a payment technology firm that promoted their identity to a new audience by running a six-day pop-up store campaign in central London.

Businesses were allowed to conduct their trade from the pop-up store with their own branding as long as all transactions were done using iZettle’s mPOS technology.

It promoted iZettle as a new choice for PoS organisations and helped the company to become associated with small and local businesses.

Visa Europe Collab

Visa Europe Collab created a campaign during London Fashion Week S/S’16 that would highlight what’s next in payment technology. Their Cashless on the Catwalk campaign promoted high fashion with contactless payment technology.

They partnered with celebrities and gave them NFC-enabled rings that allowed them to buy items directly from the catwalk. With the campaign’s success, it won the FinTech Marketing Campaign of the Year at the 2016 FinTech Innovation Awards.

Using Video & TV Ads  

Transferwise.

A finalist in the FinTech Innovation Award in 2015, TransferWise came up with a creative way to announce itself in the industry. They released The Party’s Over video ad, which showcases a big party at the Bank of Money. Like most parties, the party ended up destroying the space. In the video, TransferWise finished the party, implying that they are leading the way for financial services and disrupting the old banking industry.  

MoneySupermarket.com.

As another frontrunner in FinTech innovation, Moneysupermarket.com is a price comparison website used in financial services that used a funny TV ad to promote their website and their brand.

In the viral Dave’s #Epicstrut ad, we see Dave strutting and dancing through the streets of LA wearing short shorts and heels while the narrator shares how he was able to save money using moneysupermarket.com’s service.

The funny video stuck with audiences everywhere and made it easier for people to remember moneysupermarket.com as a brand, reaching 18,000 shares and more than 1,000,000 views on YouTube.

The first online discretionary investment and wealth management firm from the UK, Nutmeg ran a high-profile ad campaign that targeted London commuters during ISA season. They released these ads across the London underground network, rails, and billboards.

From posting ads in carriages to strategic locations such as station entrances and exits, they made the most of the lack of mobile signal underground to give commuters the time to read through these ads and reflect about their finances. They won the FinTech Marketing Campaign of the Year in the 2015 FinTech Innovation Awards.

Web Traffic & Lead Generation

Fattmerchant.

FattMerchant wanted to turn their website as their primary source of lead generation while also breaking into the merchant services industry as a reliable credit card processing company.

To do this, they integrated a stronger brand personality into their website while focusing on educating their customers and updated their social media profiles. With the launch of a new and a more responsive website that was optimised for conversion, they improved their lead generation by up to 5x in 7 months and converted up to 4x the number of contacts.  

As one of the largest financial modelling and training firms, the company recognised the need to find a better lead generation and inbound marketing tool to increase demand for their products and services.  

After partnering with HubSpot and leveraging its marketing platform, F1F9 increased their web traffic by up to 7x and generated as much as 600 new leads every month.  

Kantox is another FinTech company that offers FX management solutions for currency exchange management. It has a marketplace that makes use of a matching engine that gives customers the option to exchange currencies directly with them at mid-market rates. They used costly outbound marketing strategies that had poor lead quality return rates.

In its quest to get more leads for the business, Kantox partnered with HubSpot who helped them create an inbound marketing strategy that now generates 50% of all of its leads. Using HubSpot’s marketing platform, they noted a 10% increase in leads and a 190% increase in website traffic.

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Step Change, Unit A1/35 – 39 Bourke Rd,NSW 2015, Alexandria , Sydney, NSW, 2015 (02) 8030 8655

• Open access
• Published: 29 November 2016

FinTech in Taiwan: a case study of a Bank’s strategic planning for an investment in a FinTech company

• Jui-Long Hung   ORCID: orcid.org/0000-0002-7710-7231 1 &
• Binjie Luo 2  

Financial Innovation volume  2 , Article number:  15 ( 2016 ) Cite this article

24k Accesses

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Metrics details

A Correction to this article was published on 02 April 2021

This article has been updated

Introduction

Since 2015 is the year of FinTech in Taiwan, it is worth investigating the challenges that emerged when banks were encouraged to invest in FinTech companies for collaboration. This study aims to identify the strategic considerations in the process of searching for FinTech investment targets.

Case description

This study used a case study investigation of a top-5 bank in Taiwan. The major data sources include the meeting notes of the FinTech investment task force and interviews with the team members. Co-opetition theory was adopted as the theoretical framework and interview questions were derived from the PARTS strategies in co-petition theory. The results relate to: (1) the strategic goals of FinTech investment, (2) the added value from FinTech companies, (3) criteria in selecting candidates in the same FinTech area, (4) choosing to work as either a cooperator or a competitor, and (5) barriers from policies and regulations.

Discussion and evaluation

This study has several findings: (1) regulations and policies shape FinTech’s development; (2) banks, technology companies, and customers are not “FinTech ready;” (3) Compare top-down with bottom up strategies; (4) banks and FinTech companies have complex relationships; (5) it is unlikely that Taiwan will produce FinTech disruptors in the near future.

The findings and discussion can benefit researchers and administrators in finance-related industries. More studies are desired to observe long-term development in terms of how companies collaborate or compete in specific FinTech areas.

In January 2015, the Finance Supervisory Commission in Taiwan (TFSB) announced the “Creating the Digital Finance Environment 3.0 Project” that aims to relax restrictions on online banking, especially in online applications (Financial Supervisory Committee 2015a , 2015b , 2015c ). The first wave required all banks to offer the online financial services listed in Table  1 by the end of 2015 (Financial Supervisory Committee 2015a ). The policy was inspired by a book titled “ Bank 3.0: Why Banking Is No Longer Somewhere You Go but Something You Do ” (King 2012 ), which predicted the disappearance of most bank branches in the near future and that most financial services offered in traditional branches will be transferred to online environments (King 2012 ). A bank is no longer the only center for all financial services. E-commerce or telecommunication companies could create new forms of financial services using technology to replace the role of banks. To decrease the impacts of the coming trend, the TFSB mailed an official order to all banks in Taiwan asking all domestic banks to propose a strategic plan to adjust the structure of human resources via training or career planning to meet the changes in human resource demands in the future.

The coming trend of FinTech is a major cause of concern for the TFSB. This is because “FinTech,” a combination of “Finance” and “Technology” that refers to the combination of both domains that will lead innovative financial services to shift away from an in-house approach to relying on external providers to deliver online and mobile solutions in a timely manner. On the one hand, the disruptive innovation can initiate new businesses and bring new job opportunities. On the other hand, it damages the basis of the banking industry, which is an important stable socio-economic foundation for nearly all countries. FinTech companies can choose to be the “disruptors”—players that enter the market to compete against existing financial institutions, or “collaborators”—those primarily targeting financial institutions as customers. Banks not only have to deal with challenges from potential disruptors, but also to collaborate with technology companies to win the competition.

A recent analysis indicates that the global FinTech investment growth continues in 2016, driven by Europe and Asia (Accenture 2016 ). Global investment in FinTech ventures in the first quarter of 2016 reached $5.3 billion, a 67% increase over the same period last year, and the proportion of investments going to FinTech companies in Europe and Asia-Pacific nearly doubled to 62% (Venture Scanner 2016 ). However, the report shows that collaborative versus disruptive FinTech ventures have different investment patterns in different areas. Overall, funding for collaborative FinTech ventures, which accounted for 38% of all FinTech investment in 2010, grew to 44% of funding in 2015. In North America, the proportion of funding for collaborative FinTech rose from 40 to 60% and in Asia-Pacific, it increased from 7 to 16%. In Europe, however, the reverse trend was true. Funding for “disruptors” there rose from 62% of all FinTech investments in 2010 to 86% in 2015 (Venture Scanner 2016 ).

Since 2015 is the year of FinTech in Taiwan, it is worth investigating the challenges that emerged when banks were encouraged to invest in FinTech companies for collaboration. The single case study approach is appropriate because it provides researchers with an in-depth look at the context, organizational relationships, knowledge, and experiences of the target case (Benbasat et al. 1987 ; Cavaye 1996 ; Miles and Huberman 1994 ). This study adopts the co-opetition theory (Brandenburger and Nalebuff 1996 ) as the theoretical foundation guiding the investigation. The results can reflect a bank’s strategic planning in response to the era of digital finance. The findings and discussion can benefit researchers and administrators in finance-related industries.

Literature review

Wikipedia defines FinTech as “an economic industry composed of companies that use technology to make financial systems more efficient” ( Wikipedia nd ). FinTech weekly ( nd ) defines FinTech as “a line of business based on using software to provide financial services.” The TFSB defines FinTech companies as belonging to one of the following categories (Financial Supervisory Committee 2015c ):

Using information or network technologies to aid the business development of financial institutions to gather, process, analyze, or supply data (e.g., big data, cloud computing, machine learning, etc.).

Using information or network technologies to improve the efficiency or security of financial services or operating processes (e.g., mobile payment, automated investment advisor, blockchain technology, biometrics, etc.).

Designing or developing other digital or innovative financial services based on information or technology.

As mentioned earlier, aggregated global investment in FinTech ventures in the first quarter of 2016 reached $5.3 billion, a 67% increase over the same period last year (Accenture 2016 ). Based on Venture Scanner’s report for the 4 th quarter of 2016 (Venture Scanner 2016 ), FinTech companies can be classified into the following categories:

Banking Infrastructure (114 startups, 1.5B funding)

Business Lending (181 startups, 9.8B total funding)

Consumer and Commercial Banking (66 startups, 1.5 B total funding)

Consumer Lending (264 startups, 16.7B total funding)

Consumer Payments (182 startups, 9.5B total funding)

Crowdfunding (68 startups, 436 M total funding)

Equity Financing (137 startups, 738 M total funding)

Financial Research and Data (79 startups, 824 M total funding)

Financial Transaction Security (101 startups, 1.6B total funding)

Institutional Investing (142 startups, 781 M total funding)

International Money Transfer (59 startups, 1.5B total funding)

Payments Backend and Infrastructure (181 startups, 10.4B total funding)

Personal Finance (194 startups, 2.7B total funding)

Point of Sale Payments (164 startups, 7.6B total funding)

Retail Investing (150 startups, 1.6B total funding)

Small and Medium Business (SMB) Tools (183 startups, 7.3B total funding)

Among these categories, Consumer Lending, Personal Finance, and SMB Tools attracted the most startups, and Consumer Lending, Payment Backend, Banking Infrastructure, and Business Lending attracted the most funding. Figure  1 shows the leading companies in some of these categories (Venture Scanner 2016 ).

Leading FinTech Companies

The report aggregated data for North American, Europe, and China. When comparing actual startup and total funding numbers in Venture Scanner’s report with the TFSB’s FinTech definition, the TFSB’s blueprint differs from the actual situation in other countries.

FinTech in Taiwan

The TFSB declared 2015 as the year of FinTech by announcing a series of actions to promote its development in Taiwan. First, all domestic banks must offer twelve online financial services by the end of 2015 (Financial Supervisory Commission 2015a ). Second, the TSFB announced eleven big data application projects, including government open data (after de-identification) in real estate credit evaluation, transaction data in the stock market, personal credit card transactions, and fraud statistics, and over 900 other finance-related datasets (Data.Gov.Tw 2015 ). Third, the banks’ shareholding ratio was relaxed from 5 to 100% for FinTech company investments (Financial Supervisory Committee 2015c ). Fourth, the TSFB set up the FinTech office, promotion funds, and a startup base (Financial Supervisory Committee 2016a ). Finally, the TSFB published a FinTech white paper in 2016 (Financial Supervisory Committee 2016a ). Taiwan’s government aims to attract 5 billion TWD in total funding and at least 30 startups.

Among these actions, some are regulations that allow banks, insurers, or other finance-related companies to operate the digital finance businesses listed in Table  2 (Financial Supervisory Committee 2016a ). Among these regulations, the “Regulations on Bank and Financial Holding Company Investments in FinTech Companies” (Financial Supervisory Committee 2015c ) allows bank and financial holding companies to invest in FinTech companies and own 100% of the shares. The other regulation, “The Regulation on Information Services and Finance Technology Industries Determined by the Competent Authority as Finance-related Industries” (Financial Supervisory Committee 2015d ) further defines the scope of FinTech companies in which banks and financial holding companies can invest. Appendix A provides a detailed summary of these two regulations.

The TFSB’s FinTech Development Strategy White Paper (Financial Supervisory Committee 2016c ) outlines a strategic framework identifying the following major development dimensions (see Fig.  2 ): payment, insurance, loans, crowdfunding, investment management, and market supply (Financial Supervisory Committee 2016c ).

Strategic Framework for FinTech Industry Development

Co-opetition theory

Co-opetition describes a strategic framework that enables organizations to classify players within their industry (Brandenburger and Nalebuff 1996 ). The model adopts knowledge in game theory to observe and explain the behaviors of different kinds of stakeholders within the same industry and beyond.

Bradenburger and Nalebuff ( 1996 ) argued that cooperation and competition exist and are desirable in every industry (Levinson and Asahi 1995 ). When all players focus on market growth, then they must cooperate to increase the benefits to all players (Hill and Lynn 2003 ). At the same time, competition distributes the benefits earned by individual players depending on their market shares. The theory provides a framework to observe how interactions between players and their choices lead to different outcomes or end states of the game. In addition, it helps administrators and researchers to identify and explain the underlying mechanisms in a firm’s environment, and how the firm can change these mechanisms to their advantage.

“Value Net” is the core concept in co-opetition theory. The theory has four types of players:

Customers: Parties to which the company directs its products and services. In return, money goes from the customers to the company.

Suppliers: Parties who provide resources to the company. In return, money goes from the company to the suppliers.

Competitors: The definition depends on perspective:

◦ Customer perspective: “A player is your competitor if customers value your product less when they have the other player’s product than when they have your product by itself.” Your product behaves as a substitute for a competitor’s product—your increase in market share will directly decrease your competitor’s share.

◦ Supplier perspective: “A player is your competitor if it is less attractive for a supplier to provide resources to you when it is also supplying the other player than when it is supplying you alone.” All firms compete with other organizations for resources in quantity, quality, and price.

Complementors: The definition also depends on the following perspectives:

◦ Customer perspective: “A player is your complementor if customers value your product more when they have the other player’s product than when they have your product by itself.” Complementors are the inverse of a competitor because the demand for their products will increase the demand for your product.

◦ Supplier perspective: “A player is your complementor if it is more attractive for a supplier to provide resources to you when it is also supplying the other player than when it is supplying you alone.” When a market is small, it is difficult to get resources delivered by guessing. When the market increases, suppliers begin to adjust their offerings and make purchasing efforts easier for all acquiring firms.

Importantly, a single player can have more than one role; a player can be both a competitor and complementor simultaneously. The market players can cooperate on the “invisible” logistics side (e.g. develop common standards or return channels) and compete on the “visible” market share side.

The authors further proposed five dimensions (PARTS) to identify strategies that change the game, to a player’s own advantage.

Players: Players can use the Value Net to identify and categorize the current players in the game. A company can examine all players in the value net and determine the roles of individual players (customers, suppliers, complementors, and competitors). Bringing more players into the game can have positive effects on a company (e.g. increasing suppliers can decrease costs; extra complementors increase the value of a company’s product; and a competitor can be brought in to give customers the feeling that they have choice.).

Added value: Added value is an indicator to estimate benefits that individual players obtain from the value net. A company can identify its added value from the other players’ point of view and take action to increase this added value in order to increase profitability (e.g., a company can offer a loyalty program to enhance customer loyalty or attract more complementors to the value net to increase its own added value).

Rules: In every business, many written and unwritten rules apply. Rules can be governmental rules, contracts with suppliers, contracts with customers, and general market rules. Although many rules cannot be changed (such as governmental rules), contracts provide opportunities to change the rules on a smaller scale.

Tactics: Tactics are defined as “actions that players take to shape the perceptions of other players.” Brandenburger and Nalebuff argue that players always take rational actions in light of that player’s perception of reality. A company can influence other players’ perceptions and actions by deliberately sending out certain signals. It is necessary, however, to be aware of these perceptions to be able to influence them.

Scope: In most cases, a game is not isolated, but linked to other games via its players. A firm can extend its business to other games when it adds value to the other game and increase its profitability. On the other hand, a firm can deliberately keep two games separate when linking the games would cannibalize its traditional business. Linking and de-linking games can occur by recognizing complementary markets, via special clauses in contracts, or by influencing the perceptions of other players.

This research conducts a case study to identify the strategic considerations in the process of investing in a FinTech company. The investigation target is a top-5 bank in Taiwan. The major data sources include the meeting notes of the FinTech investment task force and interviews with the team members. Derived from the PARTS strategies, the interview questions include:

Banking industry in Taiwan

The banking industry in Taiwan is worth trillions of TWD and is highly protected and regulated by the government. It accounts for both 6.56% of GDP and 7.4% of all jobs in Taiwan. As of June 2016, Taiwan had 39 domestic banks with 3,433 domestic branches and 464 overseas branches or representative offices (see Table  3 ). The data indicate that you can find a bank branch every 3.7 and an ATM every 1.32 km 2 on average. For a small island with only 23 million people, the banking industry is an extremely highly competitive market. Overall, the development of Taiwan’s banking industry can be divided into three stages (Chiu 2011 ):

1949–1960 (the embryonic period): The loan market was established.

1961–1989 (the development period): The stock market, bond market, and foreign exchange market emerged.

1990–2012 (the consolidation period): An important period of liberalization and internationalization for the banking industry, with key deregulation including (1) allowing foreign banks to set up branches, allowing the establishment of new commercial banks, allowing the establishment of financial folding corporations, and allowing the privatization of public sector banks, etc.

To address the coming trend of digitalization in finance, the TFSB proactively announced a series of deregulations after 2014 to encourage financial innovation. Therefore, we might call 2014 the beginning of the fourth stage—the innovation period.

Policy and regulatory barriers

In Taiwan, the bank industry is highly protected and regulated; banks are prohibited from engaging in any business that does not have related policies or regulations. Therefore, when the government requested that all banks engage in innovation, they were not sure what to do at first. In addition, there are too many limitations or regulations for new startups. For example, the minimum capital for a new startup to apply for a third-party payment license is ten million US dollars. Additionally, FinTech companies cannot manufacture hardware and must derive more than 51% of their annual operating costs or operating revenue from financial enterprises (including financial holding companies, banks, securities firms, insurance companies, and their subsidiaries) ( Appendix A ). Regulations also make it difficult for foreign FinTech companies, such as P2P lenders, to enter Taiwan’s market.

Case study bank

The target bank (T bank) is under a financial holding corporation and ranked as one of the top 250 banks worldwide and among the top 5 in Taiwan. It has 190 branches, 34 overseas branches/representative offices, and over 5,000 domestic employees (Financial Supervisory Committee 2016b ). Table  4 compares T bank with other domestic banks in major business areas (Financial Supervisory Committee 2016b ).

Overall, T bank’s strength is in Corporate Finance, especially in SME loans. Compared to the other top-tier commercial banks, T bank’s personal finance business is a weakness. In 2015, T bank renamed the division of electronic finance as the division of digital banking to declare its ambitions to develop digital banking, including online banking, electronic payment, FinTech, and big data analytics. The Chairman of T bank aims to cultivate personal finance as another star business by means of FinTech and big data analytics. Therefore, the bank established the FinTech, Artificial Intelligence, Blockchain, and Maker Base task forces to search for the best solution providers or startups on the market. The team members include supervisors in the divisions of digital banking, information technology, personal finance, corporate finance, venture capital, foreign exchange markets, and compliments and legislative. These groups are led by two vice presidents and report to the President and Chairman directly. After over 7 months of effort, T bank identified the most appropriate target and completed their first investment in 2016. The task force continues to look for other suitable candidates. The next section describes the bank’s process for FinTech investment by research question.

The strategic goals of FinTech investment

Signing purchase contract with external technology vendors is very common for banks in Taiwan. However, looking for a complementor as a partner is totally a different story. It was therefore a long exploration process for T bank to determine the following strategic goals:

Look for a strategic partner rather than targeting ROI only

Look for a technology company that can co-develop unique financial services with T bank’s employees

Look for new startups or small companies with innovative expertise.

Added value from FinTech companies

The task force started with a quick survey of the list of current vendors, FinTech-related reports or contests, and recommendations from internal and external channels to compile a list that contained 36 FinTech or FinTech-like companies (Table  5 ). They then examined and discussed each company in the first round of screening and selected 16 for on-site visits.

Below describe insights from the task force by FinTech categories.

Fintech companies in the payment category can be divided into two types: Third-party payment and point of sale payment. The third-party payment companies attracted all banks’ attentions in 2015 because these companies will offer services in online, offline, and online-to-offline environments. In May 2015, the TFSB announced “The Act Governing Electronic Payment Institutions” to supervise third-party payment institutions. The act allows banks and non-financial companies to apply for third-party payment licenses. Five non-financial companies were approved in 2015 and 2016, and each of these companies has third-party payments as their core business, similar to PayPal. In addition, 10 banks (including T bank) and 12 e-commerce companies can also provide third-party payments, though this is not their core business. E-payment services are already up and running at all 10 banks, but none of the five third-party companies can offer their services until 2017. These third-payment payment companies are very welcome bank’s investment in order to form a stronger alliance. Therefore, they limit the shareholding percentage to 5–10%, in order to have more bank partners. Although the third-party payment attracted many attentions in the beginning, banks predict only one or two companies will survive due to the low profit margin. Point of sale payment is the other type of payment companies whose major customers are physical retailers. These companies mainly provide POS systems to retailers. In the past, credit card readers and POS systems are different devices and a store usually needs to prepare at four credit card readers, one pre-paid card reader, and one POS system. Due to the integration of hardware (all-in-one card reader with cloud-based POS functions) and software (integrated payment API), the all-in-one smart POS system can satisfy assorted payment needs from retailer stores. In addition, the all-in-one smart POS system can accept all kinds of payment tools, including cash, credit card, pre-paid card, gift card, and other payment types via TSM, HCE, TSP, and QR Code technologies. A well-known POS company became T bank’s first FinTech investment target. More details will be introduced later.

Banking infrastructure and system integration

The task force filtered out technology/solution providers because they felt that these companies concentrate only on their current business and are not ready for a higher-level challenge. Therefore, they selected none of companies in the banking infrastructure and system integration for online-site visits.

TFSB tended not to set up any regulations on P2P lending (Financial Supervisory Committee 2016d). In addition, TFSB encourages banks to collaborate with P2P companies on the lending business. Right now there are two P2P companies on the market ( https://www.lend.com.tw and https://lnb.com.tw/ ). Although no matter personal loan and corporate loan are not hard to be approved by banks at all, many banks, including T bank, are preparing to set up their own online lending platform instead of collaborating with P2P companies. For example, SinoPac bank’s bidmoney platform ( https://bidmoney.sinopac.com ) is the first and the only P2P platform from bank. It will be expected more similar platforms will appear in these 2 years.

Big data analytics

Big data analytics companies are hard to complete with large analytics companies, like SAS, IBM, and TaraData. Therefore, the local big data analytics companies all focus on the techniques of Chinese text mining. Chinese might be the hardest language to perform Natural Language Processing, due to its unique characteristics. Due to bank’s data contains sensitive personal information, T bank is more interested in buying or cultivating its own analytics team. These local analytics companies can be solution providers of intelligent automatic customer services and sell their products to all banks. They are not interested in becoming a specific bank exclusive company.

Blockchain is another area which attracts lots of attentions. Maicoin and Gcoin are two major companies in Taiwan with potential bank partners. In addition, TFSB regards blockchain as a crucial foundation of the FinTech industry. Therefore, TFSB is planning to set up a national blockchain for all banks. Blockchain contains two major flows, virtual currency flow and information flow. Right now banks are more interested in the aspect of information flow. Four banks will collaborate with Maicoin. Another two banks will collaborate with Gcoin. CTBC bank just announced that they joined the R3 alliance. Therefore, more investment on the blockchain from banks can be expected in the future. T bank’s chairman also assigned a taskforce to search for blockchain partners. Because related information is classified, no further information can be revealed in this article.

After the on-site visits, T bank moved on from most candidate companies for several reasons: (a) T bank would have difficulty developing any unique financial services with these companies (no added value) because they are more like solution vendors; (b) the stock price per share (PE ratio) is too high, and (c) recent analysis indicates that cash and credit cards are still the major payment tools (59 and 58.1%, respectively) (Market Intelligence & Consulting Institute 2016 ). In addition, people can withdraw/wire cash, pay transaction fees, pick up online shopping goods, and buy electronic tickets at any supermarket. With the highest density of supermarkets (over 10,000) in the world (Taiwan Today 2014 ), payment is convenient in Taiwan. Whether other payment methods can become mainstream is still under observation.

Criteria to select FinTech candidates

Since banks do not know how to design an innovative financial service using technology and technology companies do not know how to apply their knowledge to finance, T bank had difficulty identifying qualified candidates. Therefore, due to the limited number of FinTech companies available, they did not identify more than one candidate with potential in the field.

Cooperator or a competitor?

In the highly competitive market, such as mobile payments or e-wallets, T bank tended to work as a cooperator rather than a competitor. T bank regards these products as “must have” services for all banks, which they can purchase from solution vendors. Their goal is to compete with other banks on some unique financial services, such as a P2P platform for SMEs. However, they could not find a company in this area.

In Spring 2016, T bank invested in a FinTech company offering smart POS systems based on several strategic considerations. First, retailers currently tend to have more than three devices for different payment options. The smart POS system integrates all kinds of payment options in a small mobile device, which is a very attractive solution for T bank’s customers in retail. Second, T bank and the FinTech company are complementors; the latter is a major POS system provider for top retailers in Taiwan. As T bank’s strength is in SME finance, it can help the FinTech company to expand its market share to small and medium sized retailers. On the other hand, the FinTech company can assist T bank in expanding its personal finance business, a key goal, especially in issuing credit cards or affinity cards. Finally, the smart POS system contains enterprise resource planning (ERP) modules, data analytics (cloud-based), and data visualization (cloud-based) to track retailers’ daily business activities. It enables T bank and the FinTech company to develop innovative financial services and use the POS system as the customer-end interface.

Regulations and policies shape FinTech’s development

Government regulations and policies significantly shape an industry’s development. The most famous case is the influence of deregulation on the US telecommunications industry in 1982, which resulted in the industry’s liberalization (Los Angeles Times 1995 ). Thus, researchers should track how the series of deregulations will shape Taiwan’s FinTech industry development. At the same time, restrictions in the current regulations prevented some overseas FinTech companies from offering their financial services in Taiwan. Based on authors’ own observations, the deregulation will continue, though the banking industry will maintain its unique position and high government protection in the future.

Banks, technology companies, and customers are not “FinTech ready”

Compared to other countries, Taiwan is behind in the revolution of financial digitalization in terms of practical development, customer adoption, and legislation. It seems that Taiwan’s banks have been protected for too long. Banks, technology companies, and customers are not “FinTech ready.” T bank’s Chairman and President also sensed the problem and think that the best way forward is to cultivate collaborative relationships with startups. Therefore, T bank will set up a maker base and assign a group of T bank’s employees to collaborate with these companies on R&D. A follow up study of these efforts would be beneficial.

Mobile payment is another example. In 2015–2016, Apple pay, Line pay, WeChat pay, Alipay, and domestic third-party companies introduced assorted innovative payment methods via TSM, HCE, TSP, and QR Code technologies (Financial Supervisory Committee 2016c ). However, based on TFSB statistics, credit cards are still the most popular payment method. Most transactions counted as mobile payments were credit card transactions linked with apps. Among these innovative payment technologies, WeChat pay and Alipay attracted a lot of attention in 2015. With a potential 60 billion TWD in spending annually, tourists from China account for about 35% of annual tourists to Taiwan. Therefore, although only tourists from China can use these two payment options, three banks collaborate with Alipay and four banks collaborate with WeChat pay. These banks are interested in both the Chinese tourists and in cross-border e-commerce transactions and cross-border tuition payments (there are about 8,000 Chinese students studying in Taiwan). The high number of new mobile payment options opens another research topic in terms of how these payment companies/technologies collaborate or compete.

Complex relationships among banks and FinTech companies

Banks and FinTech companies have complicated relationships. T bank chose to collaborate with other banks on “must have” financial services but compete with them on unique technology-based services. The authors assume that other banks have similar strategies because some FinTech companies have refused to remain “xx bank exclusive,” especially when their products are more like “must have” services. Therefore, these companies welcome investments from banks and limit their shareholding. On the other hand, startups might like the “exclusive” approach due to the high percentage of investment from a specific bank. However, there is a potential risk that they will not gain contracts with other banks in the future.

Compare Top-down with bottom-up strategies

T bank collaborates with other banks on “must have” financial services, such as mobile payments, by collaborating with third-party payment companies so customers can link their bank accounts or credit cards with the third-party wallet or apps. Because these third-party companies aim to cultivate their own payment ecosystem, the authors call this a top-down strategy. On the other hand, the FinTech company T bank invested in has been working as a solution provider in the retail industry for more than 20 years. It has a solid buyer base and knows buyers’ needs. Obviously, the bottom-up strategy is more attractive to T bank because the collaboration can help the bank expand its current business and discover a new “blue ocean.”

Taiwan will have difficulty producing FinTech disruptors in the near future

Taiwan is not a friendly environment for FinTech startups: firms in this industry face high entrance barriers, high competition, and a market size that is not attractive to new challengers. Second, most financial services are very convenient with low service fees. Therefore, customers might feel that innovative financial services are better than services from existing banks. However, the adoption rate will be slow, just as in credit card versus mobile payments. Third, traditional financial institutions are highly protected by the government. Put another way, the government does not want disruptors because they will damage the foundations of these traditional financial institutions. Therefore, it is unlikely that Taiwan will produce FinTech disruptors in the near future. Instead, almost all FinTech companies will be collaborators aiming to provide solutions for traditional financial institutions.

The case study reveals the strategic consideration in the process of searching for FinTech investment targets. It seems Taiwan’s government aims to cultivate FinTech collaborators rather than disruptors. It is still at the embryonic stage for FinTech industry in Taiwan. Therefore, more studies are desired to observe long-term development in terms of how companies collaborate or compete in specific FinTech areas.

Change history

02 april 2021.

A Correction to this paper has been published: https://doi.org/10.1186/s40854-021-00241-5

Accenture (2016) Global Fintech investment growth continues in 2016 driven by Europe and Asia. https://newsroom.accenture.com/news/global-fintech-investment-growth-continues-in-2016-driven-by-europe-and-asia-accenture-study-finds.htm . Accessed 10 Sept 2016.

Benbasat I, Goldstein DK, Mead M (1987) The case research strategy in studies of information systems. MIS Q 11(3):369–386

Article   Google Scholar  

Brandenburger A, Nalebuff B (1996) Co-opetition. Doubleday, New York

Google Scholar  

Cavaye AL (1996) Case study research: a multi-faceted research approach for IS. Inf Syst J 6(3):227–242

Chiu LT (2011) Retrospect and prospect of financial industry development in Taiwan. Econ Res 11:171–197

Data.Gov.Tw (2015) Financial Supervisory Committee big data project http://data.gov.tw/node/12077 . Accessed 30 Sept 2016

Financial Supervisory Commission (2015a) Construct digital finance environments. http://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201501130003&toolsflag=Y&dtable=News . Accessed 21 Sept 2016.

Financial Supervisory Committee (2015b) The act governing electronic payment institutions http://law.fsc.gov.tw/law/EngLawContent.aspx?Type=C&id=1802 . Accessed 30 Sept 2016.

Financial Supervisory Committee (2015c) Regulations of bank and financial holding company investing FinTech firms http://law.banking.gov.tw/Eng/FLAW/FLAWQRY03.aspx?lsid=FL078705&keyword=10460003280 . Accessed 30 Sept 2016

Financial Supervisory Committee (2015d) Regulations of Industry of Information Service and Industry of Finance Technology Determined by the Competent Authority as Finance Related Industry http://law.banking.gov.tw/Eng/FLAW/FLAWQRY03.aspx?lsid=FL078705&keyword=10460003280 . Accessed 30 Sept 2016

Financial Supervisory Committee (2016a) Financial technology area http://www.fsc.gov.tw/ch/home.jsp?id=478&parentpath=0,7 . Accessed 30 Sept 2016

Financial Supervisory Committee (2016b) Basic financial data http://www.banking.gov.tw/ch/home.jsp?id=157&parentpath=0,4&mcustomize=bstatistics_view.jsp&serno=201105120009 . Accessed 30 Sept 2016

Financial Supervisory Committee (2016c) FinTech Development Strategy White Paper http://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201605120002&aplistdn=ou=news,ou=multisite,ou=chinese,ou=ap_root,o=fsc,c=tw&dtable=News . Accessed 4 Oct 2016.

Financial Supervisory Committee (2016d) P2P will not set up regulation http://udn.com/news/story/7239/1793803 . Accessed 10 Oct 2016.

Fintech weekly (nd) Fintech definition. https://www.fintechweekly.com/fintech-definition . Accessed 26 Aug 2016.

Hill C, Lynn L (2003) Producing human services why do agencies collaborate? Public Manage Rev 5(1):63–81

King B (2012) Why banking is no longer somewhere you go but something you do. John Wiley & Sons, Singapore

Book   Google Scholar  

Levinson N and Asahi M (1995) Cross-National Alliances and Interorganizational Learning Organizational Dynamics. 24: 50–64.

Los Angeles Times (1995) AT&T breakup II: highlights in the history of a telecommunications giant. http://articles.latimes.com/1995-09-21/business/fi-48462_1_system-breakup . Accessed 22 Oct 2016.

Market Intelligence & Consulting Institute (2016) Mobile payment investigation. https://mic.iii.org.tw/micnew/IndustryObservations_PressRelease02.aspx?sqno=427 . Accessed 30 Sept 2016.

Miles MB, Huberman AM (1994) Qualitative data analysis. Sage, Los Angeles

Taiwan Today (2014) Taiwan top for convenience store density. http://taiwantoday.tw/ct.asp?xItem=214462&ctNode=2183 . Accessed 12 Oct 2016.

Venture Scanner (2016) Financial technology startup landscape trends and insights-Q4 2016. https://www.venturescanner.com/blog/tags/venture%20scanner%20fintech . Accessed 8 Oct 2016.

Wikipedia (nd) Financial technology. https://en.wikipedia.org/wiki/Financial_technology . Accessed 11 Sept 2016.

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Authors’ contribution

J-LH: data collection, data analysis, literature review, and manuscript writing. BL literature review and manuscript writing. Both authors read and approved the final manuscript.

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Jui-Long Hung

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Regulations related to FinTech investment

Information service enterprises are firms whose main business is electronic data processing closely related to the data processing operations of financial institutions; e-commerce trading information processing involving the accounts of financial institutions; or research, development, and design of financial information systems to support the business development of financial institutions.

Financial technology enterprises are firms whose main business is one of the following:

Using information or network technologies to aid the business development of financial institutions in data gathering, processing, analysis, or supply (e.g., big data, cloud computing, machine learning, etc.).

Using information or network technologies to improve the efficiency or security of financial service or operating process (e.g., mobile payments, automated investment advisor, blockchain technology, biometrics, etc.).

The main business of the aforementioned information service enterprise or financial technology enterprise may not include the manufacture, sale, or leasing of hardware equipment. If such information service enterprise or financial technology enterprise provides hardware equipment, the purpose of the hardware equipment must be congruent with the nature of the business or data mentioned in the preceding paragraph and associated with the design of finance-related applications.

For information service enterprises or financial technology enterprises that engage in the businesses or activities provided in Point 2 and later section of the preceding point, the portion of its annual operating costs or operating revenue derived from financial enterprises (including financial holding companies, banks, securities firms, insurance companies, and their subsidiaries) and financial services shall make up 51% or more of its total operating costs or operating revenue. The preceding provision does not apply if the investment of the bank or financial holding company in said information service enterprise or financial technology enterprise is for the purpose of a strategic alliance or enhancing business cooperation, and the bank or financial holding company does not have control or material influence over the enterprise as provided in the Regulations Governing the Preparation of Financial Reports by Public Banks or Regulations Governing the Preparation of Financial Reports by Financial Holding Companies (e.g., shareholding in the enterprise is below 20%).

Banks and financial holding companies shall, within 1 month after the end of each fiscal year, report the percentage of annual operating costs and operating revenue of their invested information service enterprise or financial technology enterprise derived from financial enterprises and financial services to the competent authority for recordation. Should the percentage fail to comply with the preceding point, the bank or the financial holding company shall make adjustments to become compliant within 2 years from the year of reporting, and may apply for one extension for a period of 1 year with reasons stated if the adjustment cannot be completed within the prescribed period. If the bank or the financial holding company is still non-compliant past the prescribed and extended period, it shall submit a share disposal plan to the competent authority to reduce its amount of investment or shareholding in the information service enterprise or financial technology enterprise to not more than 5% of the total paid-in capital or issued and outstanding shares of the enterprise, or make adjustments to become compliant with the latter section of the preceding point.

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Hung, JL., Luo, B. FinTech in Taiwan: a case study of a Bank’s strategic planning for an investment in a FinTech company. Financ Innov 2 , 15 (2016). https://doi.org/10.1186/s40854-016-0037-6

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Received : 02 November 2016

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DOI : https://doi.org/10.1186/s40854-016-0037-6

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India: Case Study on the Power of Fintech Innovation

The Indian payments landscape completely transformed over the last decade, catalyzed by a shift from cash, cards, and other traditional payment methods to real-time A2A payments, powered by the UPI network and mobile apps. This globally-relevant case study on fintech innovation and disruption was fueled by a crescendo of forces including government policies, banking infrastructure upgrades, and the influence of mobile phone technologies. Figure 1 shows the rapid ascent of UPI-powered mobile payments while usage of cash, cards, and prepaid wallets diminished in share of wallet. Within this article, we tell the story of the rapid transformation of payments in India, and what the future might hold.

Mobile Payments Disruption

Prior to UPI, Indian fintechs were already driving the market towards mobile payments, a push that started with the introduction of digital wallets powered by prepaid accounts such as the Paytm Wallet in 2014. These mobile wallets were propelled by India’s demonetization policy, a large scale macro-economic exercise implemented by the government to combat corruption and push for digital payments. In November 2016, the government of India discontinued the acceptance of all existing currency notes overnight (larger than Rs. 500), with the motive of replacing them by printing new notes. The policy led to a shortage of cash in the country forcing consumers to find digital alternatives. This created the perfect opportunity for fintechs such as Paytm to fill this gap by offering digital propositions designed for both consumer and merchant. Digital wallet adoption rate skyrocketed as consumers became more comfortable with mobile payments.

UPI Payments Explained

The introduction of UPI turbo-charged the pace of innovation and disruption in India. Unified Payments Interface or UPI, launched by the National Payments Corporation of India (established by the Reserve Bank of India) in 2016, is an account-to-account payment system that enables consumers and merchants to send and receive payments with real-time settlement. Currently UPI accounts for about two in every three retail non-cash transactions in India.

UPI is not an end-user product (not a mobile app), but a payment network, used by fintechs and banks who develop and distribute the mobile apps that power payments through the UPI network. Users can easily enable this payment method by creating a unique UPI identification key that is linked with the user’s bank account and mobile number. Many mobile payment apps such as PhonePe, GooglePay, and Paytm (among others) support UPI sign-up, initiation or receipt of payments to and from users’ bank accounts. For P2P transactions, users can simply use the mobile number linked with a UPI ID to transfer money instantly making the user experience extremely quick and frictionless.

Figure 3 illustrates the primary use cases for C2B (merchant) payments, which are enabled by QR codes. There are two types of QR codes used with UPI: Dynamic QR and Static QR. Larger merchants that have integrated payments at their point-of-sale, will utilize the dynamic QR code, which is generated upon billing and presents the customer with the exact amount to be paid. As software embedded payments are still relatively nascent in India, and limited to larger enterprises, static QR codes provide a simpler way for small merchants to receive payments without having an integrated POS system. The static QR only contains the UPI ID of the merchant and customer needs to manually input the amount to be paid. The key success factor for achieving a frictionless experience is that UPI transactions are real-time, allowing both consumers and merchants to receive instant notification of payment completion.

Government Incentive and The Real Cost of UPI

UPI’s rapid growth as a preferred means of C2B payments is fueled in part by a government policy for zero-cost UPI payments, which today, are free for both consumers and merchants (a policy introduced on 1 Jan 2020). The government does subsidize market participants, but this subsidy is small in comparison to the actual costs of the ecosystem (subsidies of c.$295 million in 2022 to merchant acceptance participants falls vastly short of the estimated total costs that are in excess of $1 billion). In the recently announced Budget for FY 2023-2024, the government reduced the subsidy amount to less than $200 million. According to ecosystem cost estimates from the Reserve Bank of India (RBI), on average, a C2B UPI transaction generates a total cost of approximately 0.25% considering the roles of the different stakeholders in the value chain. We break-down RBI’s cost estimates in Figure 4.

Due to India’s current zero-merchant-discount-rate policy, UPI C2B payments are unusually unprofitable for fintechs and banks. PSPs and app providers such as PhonePe, GooglePay, and Paytm (shares shown in Figure 5) are forced to find other sources of revenue such as bill payments and most notably, various forms of embedded credit to consumers and merchants. The lack of payments profitability is one reason why fintechs such as Paytm still struggle to achieve profitability. Paytm reported a -30.5% EBITDA margin for FY 2022, despite its scale and relatively long tenure in the market. The company did however, report a positive EBIDTA margin of c. 1.5% for the first time in Q3 FY 2023, which is attributed largely to expense reductions.

Some Indian market participants expect the ‘zero-cost’ policy to fade, resulting in more natural economic incentives for parties involved in C2B UPI transactions. Merchants continue to lobby in favor of the current policy, which seems to be working as the Indian Ministry of Finance announced last year that UPI is a digital good and the government has no intension of changing the current zero-cost policy. For now, there remains a tension between the massive fintech potential of UPI and the lack of payments profitability for UPI service providers.

Growth of Mobile Payments and Future Implications

India is now the global market leader for real-time A2A payments, but certainly not the only country which has seen a massive uptake in digital payments, as shown in Figure 6. This trend is replicated in other markets such as Brazil and Thailand, where A2A banking infrastructure combined with mobile means of payment are powering disruption. We do not see the same pace of A2A + mobile disruption in more mature western markets. This is a classic example of the ‘leapfrog effect’ in payments where less-developed markets evidence far more rapid innovation and disruption versus mature markets, where behaviors linked to cards are more deeply entrenched (formed over decades).

Countries around the world are drawn to the India (UPI) case study as they aspire for efficient, digital payments and alongside financial inclusion. The National Payments Corporation of India (NPCI) is working to internationalize UPI, recently signing a memorandum of understanding with 13 countries including Singapore, Thailand, France, Netherlands and the U.K. to enable acceptance of UPI outside the countries. NPCI is working with payment providers such as Worldline in Europe to implement Indian payment methods including RuPay and UPI in countries including Netherlands, Belgium and Switzerland. Through this partnership, Worldline’s merchants in Europe will be able to accept UPI payments at the point-of-sale using QR codes.

The Reserve Bank of India also recently announced an agreement with the Monetary Authority of Singapore allowing interoperability between UPI and PayNow (Popular alternative payment method in Singapore). This allows users of both instant payment systems to use the other seamlessly without additional sign-ups and send money cross-border. This alliance is a unique global case study on interoperability of A2A schemes, and one which we expect to be replicated in other markets.

India is a perfect example of the power of fintech to transform an economy and the day-to-day lives of people. In less than a decade, India went from a wide-spread lack of financial inclusion to a country that is now leading the world in A2A-powered mobile payments. This success is the result of government policy working hand-in-hand with banking and fintech innovation. Going forward, however, the fintech community must tackle challenges posed by zero-cost payments, as while Indian consumers and merchants benefit from payments innovation, shareholders are still searching for return on investment.

Please do not hesitate to contact Joel Van Arsdale at [email protected] with comments or questions.

Sameer Verma

Joel Van Arsdale

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Paytm Case Study: The Journey of India’s Leading FinTech Company

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Financial Technology popularly termed as Fintech sector has flourished exponentially after the demonetization in 2016. According to a report, India’s Fintech industry was valued at US $50 billion in 2021 and is expected to reach the value of US $150 billion by 2025 . And if we talk about the leading players in the industry, Paytm comes to the top of the list unarguably.

Paytm is India’s leading financial services platform offering digital payments ranging from mobile recharge to bill payments (credit cards, DTH, electricity and utility bills). Along with traditional mobile banking, Paytm also acts as a gateway for ticket booking (IRCTC, IPL, etc.) and offers e-commerce services as well. Along with India, Paytm is operable in Japan and Canada and is also available in 11 Indian languages, serving more than 350 million registered users.

In this Paytm case study, we have covered the growth story of Paytm from being just one of the online platforms for recharge payments to becoming a lead disruptor of India’s fintech sector.

Paytm – O rigin & Journey

Although Paytm was founded by Vijay Shekhar Sharma in 2010 in the NCR region of New Delhi, Noida, in actual terms, it started way before. Vijay Shekhar Sharma launched One97 Communications, the parent company of Paytm back in 2000. Paytm started as a normal mobile recharge website and over time it also introduced DTH recharges and landline bill payments.

A quick timeline of Paytm’s journey is given:

2010 : Paytm was launched as a mobile recharge platform

2013 : Paytm added DTH Recharge, Data Card, and Landline bill payments

2014 : Paytm launched Gateway Payments for IRCTC and Uber

2015 : Paytm became India’s first Fintech unicorn after funding from Alibaba Group and Ratan Tata

2016 : Paytm introduced the Payments Bank

2017 : After demonetisation, Paytm rolled out UPI (Unified Payments Interface)-based payments

2018 : Paytm First Games owned by Paytm and Alibaba-backed AG Tech Holdings was launched

2019 : Paytm launched QR/POS/Gateway combined services

2021 : One97 Communications enters Indian Stock Market by launching its IPO

2023 : Paytm Payments Bank launches UPI Lite

Major Paytm Services

As we move further with the Paytm case study, let us look at some of the popular products & service offerings by Paytm –

Paytm Insider

Paytm Insider is an online ticket booking platform co-owned by Paytm and Insider.in. It is the one-stop ticketing solution for popular events, concerts, cricket matches, and product fests happening in the city.

Paytm Mall is an e-commerce store launched by Paytm in 2017. It is a B2C platform intended to provide a Bazaar-like feel to the customers by choosing from over 1.4 lakh listed items. Paytm Mall takes inspiration from China’s biggest B2C company, Tmall. It raised over $200 million from Alibaba and SAIF partners in a highly anticipated funding round in March 2018.

Paytm Payments Bank

Paytm Payments Bank, after payments bank by Airtel and India Post, is the third payments bank in India. Payments Bank by Paytm received approval from the Reserve Bank of India in 2015 but was officially launched in November 2017. It provides complete banking services ranging from Savings Accounts to Loaning facilities. It also offers Paytm Wallet, which can be used as a mobile payment method while paying at any QR, online merchant or any digital transaction.

Paytm Money

Paytm Money is a SEBI-registered stock brokerage and advisory platform offered by Paytm. It was launched in 2017 and provides free demat account opening, trading and investment in Mutual Funds, the Stock market and also NPS retirement funds. 

Revenue Model of Paytm

This Paytm case study highlights the major revenue sources of Paytm, which are as follows:

Interests from Escrow Account: Paytm secures the wallet money of its users in an escrow account linked with a nationalised bank. With this, Paytm makes around 4-6% of interest easily.

Commission from Merchants: Paytm charges nominal commissions from users as well as the merchants while making payments, purchasing digital gold or investing in stocks.

Advertisements: We often see pop-ups of offers and deals when we open the app, Paytm charges the companies and businesses for running those ads.

Marketplace: Paytm has a dedicated e-commerce store which brings a fine chunk of their revenue. Paytm Mall has a commission linked with the sellers.

Gateway Fees: Many platforms like IRCTC have a separate payment gateway linked with Paytm. In such cases, a gateway payment is applied.

Paytm Stats

*All values in Cr

Paytm has generated a revenue of around Rs. 7990 Cr in 2022-2023, which is a growth of over 3000Cr from its previous year’s earnings. After its listing on the NSE, it has given a CAGR of around 69% in its revenue.

PROFIT/LOSS

So, we can see that Paytm has been making significant losses over the years. High Operation costs and Customer acquisition costs are the main reasons for the above losses. Additionally, Paytm is often struggling with Government regulations as well which inhibits their income.

Major Acquisitions

Paytm acquired a majority stake in event booking and ticketing platform, Insider.in owned by OML Entertainment in June 2017. The deal was finalised for an amount of $5.42 million (44 crores).

NightStay is a hotel-booking startup based out of Noida. Paytm acquired Nighstay in a $20 million (160 Crores) deal in 2019.

Paytm acquired complete stakes in CreditMate, a Mumbai-based digital lending startup in October 2021, a few days before its stock market inaugural. The amount of acquisition was however undeclared.

Paytm is one of the biggest fintech companies in India with a wide range of services on board. Since its inception in 2010, Paytm has been delivering high-end digital banking solutions. As a result, it is among the top 3 companies with maximum UPI transaction volumes in India. Additionally, Paytm is working on improving the infrastructure of digital payments in the country and making it even more robust.So, we hope you find this Paytm case study helpful and informative.

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What determines FinTech success?—A taxonomy-based analysis of FinTech success factors

• Research Paper
• Open access
• Published: 19 May 2023
• Volume 33 , article number  21 , ( 2023 )

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• Oliver Werth   ORCID: orcid.org/0000-0002-6767-5905 1 ,
• Davinia Rodríguez Cardona 2 ,
• Albert Torno 3 ,
• Michael H. Breitner   ORCID: orcid.org/0000-0001-7315-3022 2 &
• Jan Muntermann   ORCID: orcid.org/0000-0002-1470-6042 4  

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Value creation in the financial services sector has been fundamentally transformed by digitally born financial technology (FinTech) companies. FinTech companies synthesize information systems with financial services. Given its disruptive power, the FinTech phenomenon has received great attention in academic research, practice, and media. Still, limited systematic research provides a structure and holistic view of FinTechs’ success. Aiming to enhance understanding of the factors enabling FinTech success, we classify success factors across extant scientific literature on distinct FinTech business model archetypes. Our analysis reveals that the “cost–benefit dynamic of the innovation,” “technology adoption,” “security, privacy, and transparency,” “user trust,” “user-perceived quality,” and “industry rivalry” are crucial factors for FinTech success and can be seen as “grand challenges” for the FinTech ecosystem. In addition, we validate and discuss our findings with real-world examples from the FinTech industry and two interviews with stakeholders from the FinTech ecosystem. Our study contributes to the knowledge of FinTechs by providing a classification system of success factors for practitioners and researchers.

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Introduction

Success and its associated concepts have been identified for their high importance in information systems (IS) and management research (e.g., Petter et al., 2013 ; Thompson et al., 2018 ). Success can be determined through a collection of relevant factors that a company or industry should focus on to achieve a competitive performance (Petter et al., 2013 ; Rockart, 1979 ). Given the interconnection between success and competitive performance, recent studies have found empirical evidence supporting the association between venture success and “the design or architecture of the value creation, delivery, and capture mechanisms” (Teece, 2010 , p. 172) of a company, framed through the conceptualization of its underlying business model (e.g., Böhm et al., 2017 ; Weking et al., 2019 ).

In the financial industry, the value creation process has been fundamentally transformed into innovative business models that integrate digital technologies and concepts (Imerman & Fabozzi, 2020 ). Furthermore, this convergence between IS and financial services is enhanced through “born-digital” financial technology companies (FinTechs). Due to their digital nature, FinTechs can create new value propositions, e.g., increasing financial inclusion and decreasing income inequality (Demir et al., 2020 ; Lagna & Ravishankar, 2021 ) or reshaping the financial system and the monetary policy implementation through financial disintermediation (Mumtaz & Smith, 2020 ). Given this social and economic disruptive power, the sustainability of the FinTech phenomenon is receiving increasing attention in academic research and growing relevance in practice (Klein et al., 2020 ; Omarova, 2019 ).

Looking closely at the FinTech market, the number of FinTechs rose from around 12,000 in 2018 to 26,000 in November 2021 (Statista, 2021a ). In addition, FinTech adoption rates have significantly increased in several countries like the USA and the UK (Insider Intelligence, 2021 ; Statista, 2021a ). Pre-COVID-19 pandemic investments in these ventures raised significantly until 2019 to 215.1 billion US Dollars (Statista, 2021b ). Most recent data conclude that the investment volumes are higher than the pre-pandemic level (226.5 billion US Dollars in 2021) and seem to continue in 2022 (107.8 billion US Dollars after the first half of 2022) (Statista, 2021b ). Therefore, the FinTech market is still an attractive business field for investors and founders, and customers.

However, failure rates of FinTechs are approximately 75% (The Fintech Mag, 2022 ) and 87%, for example, in Germany within 3 to 6 years (Stuckenborg & Leker, 2019 ) after the founding. In the past, the role of FinTech and the survival of such companies were described as a “FinTech Bubble” that would burst (Dratva, 2020 , p. 66). Many FinTech companies face market or product risks (Buckley & Webster, 2016 ) and a loss of valuation, like in the case of Klarna (Fintech Magazine, 2022 ). These situations challenge FinTechs to maintain their survival in the market. Accordingly, (new) FinTechs must meet success factors (SFs) to remain attractive to investors and customers, especially in the first years of founding. FinTech survival through a provision of a constant flow of venture capital, high liquidity, and profits can avoid failure in this innovative service ecosystem (Stuckenborg & Leker, 2019 ).

SFs for FinTechs have been previously stated as an interesting research field that contributes to developing successful FinTech business models (Gomber et al., 2017 ). As a result, well-grounded knowledge and the consideration and possible prioritization by managers and investors of SFs result in a constant flow of venture capital and retain the survival of FinTech business models (e.g., Kolokas et al., 2022 ; Laidroo & Avarmaa, 2020 ; Nicoletti, 2017 ). In contrast, the still incipient integrative academic literature on success research in FinTech indicates a fragmented understanding of the SFs that contributes to successful FinTech business models (e.g., Imerman & Fabozzi, 2020 ; Werth et al., 2019 ). Therefore, these businesses and entrepreneurial SF need to be discovered comprehensively over the heterogeneous FinTech market. An examination and well-justified identification of potentially relevant SF for FinTechs is required. Guided by these motivations, the following research question (RQ) is addressed in this study:

RQ: Which theoretically grounded factors are potentially relevant for FinTech venture success across distinct FinTech archetypes and business model dimensions?

To answer our RQ, we create a literature search-based taxonomy according to the methodology proposed by Nickerson et al. ( 2013 ). This allows us to detect theoretically grounded factors previously identified by past research as relevant for FinTech venture success. We contribute to the FinTech and IS literature by providing a taxonomy that can explain the differences and similarities of objects and uncover and classify non-existent object configurations or knowledge gaps (Muntermann et al., 2015 ). As a result, the taxonomy can serve as an artifact that can be used to solve practical problems, i.e., the identification of potentially relevant SFs for FinTechs (Kundisch et al., 2021 ). We utilize the scientific literature about SFs for FinTech venture success and classify it across distinct FinTech business models identified by Eickhoff et al. ( 2017 ). Following the guidelines for taxonomy evaluation by Kundisch et al. ( 2021 ), we demonstrate the applicability of our taxonomy with a case-based taxonomy validation and discussed our findings for usefulness with two individuals from the FinTech ecosystem. From a theoretical perspective, our results and conclusions can support further theory-building processes for conceptualizing SFs across FinTech business models and serve as a vantage point for further systematic investigations in this area. Practitioners can use our results to compare their business models and consider realigning as well as prioritizing the allocation of resources in key business areas. In addition, our study serves as a discussion and supplementary information base among stakeholders, e.g., venture capitalists, about relevant SFs. In summary, our study generates a meaningful knowledge base for all involved and interested stakeholders in the FinTech ecosystem.

The rest of this paper is structured as follows: Firstly, we define SFs and describe their relationship to FinTech business models. Afterward, we explain our research methodology and data collection procedure. Next, real-world examples from the FinTech industry are discussed using archetypes and dimensions of the FinTech business. To confirm the relevance of the SFs provided, we present and discuss our findings with two individuals from the FinTech ecosystem. Furthermore, theoretical, methodological, and practical implications are presented. Lastly, we provide limitations, future research directions, and concluding remarks.

Domain background about success factors and FinTechs

Success is defined as the “accomplishment of an aim or purpose” (Oxford Dictionaries, 2022 ) or the achievement of “a satisfactory/favorable outcome” (Ain et al., 2019 , p. 7). SFs, in the business context, are certain issues that determine a firm’s success with its products or services in the market. We follow Thompson et al., ( 2018 , p. 75), who define SFs as “the strategy elements, product and service attributes, operational approaches, resources, and competitive capabilities essential to surviving and thriving in the industry.” Organizations directly influence these factors, which corresponds to an internal view of the SFs. In line with other definitions, including those of Rockart ( 1979 ) and David and David ( 2017 ), we also consider external factors, e.g., environmental factors, as relevant to success because not considering these factors could lead to detrimental effects on the competitive success of FinTechs. While SFs are often labeled in literature with the prefix “critical” (e.g., Freund, 1988 ; Rockart, 1979 ) or “key” (e.g., David & David, 2017 ; Thompson et al., 2018 ), we use the term “success factor(s)” without any prefix, because we do not intend to rank these factors. Instead, our goal is to provide a well-justified list of relevant factors that influence the success of FinTechs.

SFs should be few and controllable because they aim to measure a firm’s competitive advantage or success within an industry, e.g., through strategic analysis tools (Thompson et al., 2018 ). However, the main challenge in developing these success measuring tools, e.g., the Competitive Profile Matrix (CPM), is to identify the respective underlying SFs of the industry (Bhattacharjee, 2015 ). For example, research on SFs for technology-based startups has identified some common categories of SFs, e.g., “organizational, individual and external factors” (e.g., Santisteban & Mauricio, 2017 ), “advantage of the radical innovation, characteristics of the organization, characteristics of the entrepreneur” (e.g., Groenewegen & de Langen, 2012 ), or “accounting, market, and stakeholder-based factors” (e.g., Soto-Simeone et al. 2020 ). While these abstract factors may influence tech startups in general, there is a consensus that industry-specific research is required to determine the nature of SFs in each specific business context (Gazel & Schwienbacher, 2020 ; Soto-Simeone et al. 2020 ). Hence, this study addresses the challenge of identifying relevant SFs in the FinTech industry across different business model archetypes.

The phenomenon known as FinTech can be described as financial innovations enabled by information technology (IT) resulting in new financial instruments, services, and/or intermediaries (Arner et al., 2016 ). To characterize the different levels of novelty in FinTech, Gomber et al. ( 2017 ) describe two degrees of FinTech innovation, i.e., “sustaining FinTech” and “disruptive FinTech.” Sustaining FinTech comprises financial services incumbents incorporating information technologies to maintain their position in the market, while disruptive FinTech comprises new market competitors providing novel digital financial products and services. In addition, Gomber et al. ( 2018 ) explained that besides sustaining and disruptive FinTech, incremental, product-supplementing, and radical, new product-generating, FinTech innovations exist. We decided to follow the definition of FinTech by Eickhoff et al., ( 2017 , p. 2), given that this definition is conceptualized at the business model level and is thereby consistent with the level and context of our analysis. Consequently, we understand FinTech as the companies that “operate at the intersection of financial products and services and IT. They are usually relatively new companies (often startups) with their innovative product or service offerings” (Eickhoff et al., 2017 , p. 2). In parallel, research on SFs for technology-based startups has identified some common categories of SFs compared to traditional startups, e.g., “organizational, individual, and external” factors (e.g., Santisteban & Mauricio, 2017 ) or “advantage of the radical innovation, characteristics of the organization, and characteristics of the entrepreneur” (e.g., Groenewegen & de Langen, 2012 ). While these abstract factors may influence tech startups, there is a consensus that industry-specific research is required to determine the nature of SFs in each specific business context, e.g., within financial services (Gazel & Schwienbacher, 2020 ; Soto-Simeone et al. 2020 ). Accordingly, FinTech startups differ from traditional business models and high-tech startups because of their integrative nature in technological, entrepreneurial, and finance business contexts. For example, past research indicates that incumbent partnerships with traditional financial services providers are relevant since they are important for the short- and middle-term survival to acquire a sustainable pool of customers (Laidroo & Avarmaa, 2020 ; Werth et al., 2019 ).

Depending on the value configuration of the underlying FinTech business models, FinTech innovation can take the form of (i) new customizable, easy-to-use, and efficient products; (ii) new forms of production that minimize risks or costs; (iii) new customer interfaces or distribution channels; (iv) new markets and customer segments; and/or (v) new technology-driven business models (Eickhoff et al., 2017 ; Gomber et al., 2017 ). To better understand the value creation mechanisms of FinTechs, academics have developed diverse taxonomies about FinTech business models from different perspectives. Gimpel et al., ( 2018 ) presented a taxonomy of the characteristics of consumer-oriented FinTech business models using statistical techniques. A study from Beinke et al. ( 2018 ) developed a taxonomy to identify the business model elements in FinTechs that use Blockchain technology. Nagel et al. ( 2019 ) proposed a taxonomy of these Blockchain-based business models specifically for smart cities. Conversely, Drasch et al. ( 2018 ) identified 13 dimensions of cooperation patterns between FinTechs and banks using a taxonomic approach, and Imerman and Fabozzi ( 2020 ) presented a taxonomic structure of the Fintech ecosystem by unifying the concept of digital transformation with the relevant functional areas and emerging technologies for FinTech. Meanwhile, using a clustering-based approach, Eickhoff et al. ( 2017 ) empirically examined 2040 FinTechs from the Crunchbase database. As a result, Eickhoff et al. ( 2017 ) identified ten clusters of FinTech business model archetypes, e.g., cryptocurrency or payment services, that serve as a base for our analysis of FinTech SFs. These FinTech business model archetypes are a starting point for our taxonomy development process.

Methodology and data collection procedure

We conduct a taxonomy-based content analysis to generate insights into the factors enabling FinTech success. Figure  1 thereby shows the adapted taxonomy development method of Nickerson et al. ( 2013 ) and the methods used, which serves as the foundation of our research approach. We follow the methodological approach of Nickerson et al. ( 2013 ) because this taxonomic approach is connected to an iterative nature aimed at reducing the complexity of scattered information through the integration of theoretical knowledge (deductive iteration) and empirical evidence (inductive iteration). Therefore, it is a suitable approach to guide our literature-based study to distillate findings and structure the existing knowledge on FinTech success (Szopinski et al., 2019 ). Generally, in empirical-to-conceptual iterations, “the researcher identifies a subset of objects that he/she wishes to classify” (Nickerson et al., 2013 , p. 345). Conceptual-to-empirical approaches aim to conceptualize the dimensions of a (preliminary) taxonomy from previous knowledge, e.g., literature, without examining actual objects (Nickerson et al., 2013 ).

Adapted taxonomy development method by Nickerson et al., ( 2013 )

First, the meta-characteristic needs to be determined, which is “the most-comprehensive characteristic” and “serves as base for all other characteristics” (Nickerson et al., 2013 , p. 343). Furthermore, the intended users, i.e., researchers and practitioners interested in FinTech business models and SFs, must be considered. To be as comprehensive as possible regarding the FinTech market, we use the FinTech business model archetypes presented by Eickhoff et al. ( 2017 ). Guided by these facts and our RQ, we define our meta characteristic as “the relevant SFs for FinTech venture success located in the scientific literature for different FinTech business model archetypes.” After outlining the meta-characteristic, ending conditions must be determined, ending the taxonomy development if met. We adopted all objective (e.g., “no dimensions or characteristics were merged or split in the last iteration of the taxonomy process”) and all subjective (e.g., extendable nature of the taxonomy) ending conditions according to Nickerson et al. ( 2013 ). We followed a conceptual-to-empirical approach as a starting point and subsequently refined the taxonomy by examining and classifying a set of representative objects obtained through ten lateral systematic literature reviews corresponding to the ten FinTech business model archetypes developed by Eickhoff et al. ( 2017 ), as shown in Fig.  2 . Based on the guiding principles of Webster and Watson ( 2002 ) and Wohlin ( 2014 ), we performed both a keyword and a forward–backward literature search (Hinde & Spackman, 2015 ), which we further complemented with an author and similarity search as shown below:

Literature review procedure

The determination of the representative keywords has been accomplished by considering the FinTech business model archetypes established by Eickhoff et al. ( 2017 ) and the keywords identified by Cziesla ( 2015 ) throughout their literature analysis of the digital finance sector. We also used these keywords as umbrella terms to identify additional keywords mentioned in the academic literature. We searched for scientific articles using the set of keywords in Table 6 in the appendix in conjunction with the search term “success” in different databases.

Given the interdisciplinary nature of the topic, our examination of scientific literature covered a total of 118 peer-reviewed scientific journals and ten conference proceedings in the fields of IS, finance, and banking (BA-FI), strategic management (SM), as well as technology, innovation, and entrepreneurship (TIE). The scientific journals and conference proceedings were retrieved through five publisher databases (Sturm & Sunyaev, 2017 ): ACM Digital Library, AIS Electronic Library (AISeL), EBSCOhost, ScienceDirect, and SpringerLink. In addition to defining the relevant keywords, we delineated a set of inclusion criteria to be fulfilled. To be included in our taxonomy-based content analysis, scientific articles must (i) allude to determinant factors of success for any FinTech business model archetype (Eickhoff et al., 2017 ) and fulfill the following inclusion criteria: (ii) be published in English, (iii) between January 2008 and June 2020, and (iv) in recognized peer-reviewed academic business (i.e., BA-FI, SM, TIE) and IS journals or conference proceedings (Hennig-Thurau et al., 2022 ).

The selection process to identify the representative sample of scientific articles to be examined in the content analysis followed the same systematic procedure depicted previously in Fig.  2 . In the stage corresponding to the keyword-based search, we observed scientific articles containing our keywords in their abstracts and/or title. In this initial set ( X 1 ), we identified 37,815 potentially eligible research articles fulfilling the first three inclusion criteria. In the second stage, the eligibility of the initial set was narrowed down by eliminating duplicate articles and applying a relevance check. This approach allowed us to limit our initial sample to a set ( X 2 ) of 408 scientific articles, potentially fulfilling the fourth inclusion criterion. To ensure that only articles relevant to the success of FinTech are included in the final set of articles, we performed a full-text review of the potentially relevant articles. After excluding all irrelevant articles for our analysis (e.g., non-FinTech relevant articles, randomly mentioned in the abstract, keywords, or articles focusing only on technical aspects of digital technologies), our sample was reduced to 215 relevant articles.

To enhance this pool of relevant articles, we conducted forward, backward, author, and similarity searches. The forward, author, and similarity search strategies used Google Scholar. With the forward search, we identified five additional relevant articles that quoted the scientific articles found in the former search stage (Wohlin, 2014 ). With the author search, we found five additional relevant articles by the most important authors. With the similarity search, we found three additional relevant articles similar to the most important articles found before. The backward search was applied by analyzing the reference lists of the articles obtained from the previous search phases; through this approach, we identified four additional relevant articles. Within these procedures, we found a total of 17 additional articles, which fulfill all inclusion criteria.

As a result, we identified a final sample ( X 3 ) of 231 research articles fulfilling all inclusion criteria (alternative trading venues: n  = 87, payment services: n  = 76, insourcer of sub-processes: n  = 20, lending community: n  = 19, cryptocurrency: n  = 15, co-creator of financial analysis: n  = 7, robo-advisor: n  = 4, and information aggregator: n  = 3). For the FinTech business model archetypes “ financial markets intermediary ” and “information extractor,” we did not find articles that fulfill all of our inclusion criteria. A list of all relevant papers identified and analyzed in our study is available in the appendix, Table 5 .

Taxonomy-based content analysis of FinTech success factors

Our taxonomy-based analysis aims at structuring the knowledge on FinTech success scattered in the scientific literature on distinct FinTech business model archetypes. Hence, the first iteration of our taxonomy-based process implements a conceptual-to-empirical approach, followed by six empirical-to-conceptual paths in the form of an iterative content analysis of research articles related to FinTech success that have been identified in the previous section. All iterations were performed manually in line with the taxonomic process and ending conditions (Nickerson et al., 2013 ). Below, we outline the deductive approach to conceptualize our preliminary taxonomic structure and the iteration paths carried out during the development process of our final taxonomic structure of FinTech SFs:

1st iteration

The first iteration of our taxonomy-based process implemented a conceptual-to-empirical path to deductively conceptualize a preliminary taxonomic structure by subtracting dimensions and characteristics from the scientific literature on three axes connected to our meta-characteristic: business model research, SF research, and the FinTech business model taxonomy of Eickhoff et al. ( 2017 ). So far, this taxonomy offers the most comprehensive insight into the entire landscape of FinTechs and their corresponding business models. Therefore, we adopted the FinTech business model archetypes identified by Eickhoff et al. ( 2017 ) as a base for our analysis to draw the dimensions of (i) product/service offering, (ii) dominant technology component, (iii) delivery channel, (v) target customer, (v) revenue stream, and (vi) value proposition. These dimensions have their theoretical foundations in the knowledge field of business models (e.g., Alt & Zimmermann, 2001 ; Osterwalder et al., 2005 ), but their relevance in the FinTech context has been validated by Eickhoff et al. ( 2017 ). In line with Thompson et al. ( 2018 ), other aspects such as strategy elements, operational approaches, resources, and competitive capabilities are also success components. We, therefore, deduced the dimensions (vii) strategic factors from Chesbrough and Rosenbloom ( 2002 ), (viii) operational factors from the seminal business model research publications of Osterwalder et al. ( 2005 ) and Zott et al. ( 2011 ), (ix) cost factors and (x) stakeholder factors from Osterwalder and Pigneur ( 2010 ) along with Al-Debei and Avison ( 2010 ); as well as the dimension of (xi) input resources from Hedman and Kalling ( 2003 ). We chose the latter dimension under the premise that the efficient utilization of input resources like human capital as well as data and information is especially relevant within the FinTech industry. Furthermore, the technology level used can be seen as an industry-specific SF (Alt & Zimmermann, 2001 ), especially in industries like FinTech, where business innovation is enabled by IS (Eickhoff et al., 2017 ). DeLone and McLean ( 2003 ) state that effective IS success depends on technical and semantic success. These, in turn, produce net benefits that impact the use of the service/information produced and the user’s attitude toward the system characteristics. Based on this, we derive from the literature on IS success (e.g., Ain et al., 2019 ; DeLone & McLean, 2003 ; Petter et al., 2013 ) the dimensions (xii) user factors and (xiii) technological factors. Lastly, to consider external factors that can influence the competitive success of FinTechs (David & David, 2017 ; Rockart, 1979 ), e.g., to gain and maintain a competitive advantage, we incorporate the dimension (xiv) environmental factors. As a result, we deducted a set of 14 dimensions in this iteration. To broaden these dimensions, we compounded further related characteristics from our knowledge and experience accumulated through academic conferences, scientific publications, and the analysis of diverse digital transformation case studies in the financial sector. Table 1 presents the deductive dimensions and characteristics as well as primary scientific papers used as their conceptual bases.

2nd–7th iteration

In six inductive empirical-to-conceptual iterations, we examined all relevant research articles and identified the factors related to FinTech success. In these seven iterations, we carefully read every paper, i.e., the data, that we found per archetype, and checked the paper results for relevant SFs and related content. Consequentially, we checked the scientific articles for relevancy. Possible SFs mentioned by the authors of the papers must be directly connected to the respective archetype. If SFs were identified, we considered them for further analysis. We used MAXQDA 2020 and Microsoft Excel as supporting software for this qualitative content analysis. Subsequentially, thereby classified the found factors into the deductive initial taxonomy to refine it, e.g., by removing non-descriptive elements. An overview of the examined objects (scientific articles) and the dimensions during the taxonomy development process is provided in Fig.  3 . A detailed description of the applied steps at the characteristic and dimensional level and an overview of the subjective and objective ending conditions fulfilled in each iteration are provided in the appendix, Tables 7 and 8 , respectively. Since we did not modify the dimensions and characteristics in the seventh iteration and the objective and subjective ending conditions were fulfilled, we ended the taxonomy development process.

Dimensions development process

With our taxonomic process, we could classify potentially determinant FinTech SFs from academic literature. We observe that FinTech SFs, identified by researchers, can be classified and categorized into seven dimensions: (i) strategic factors, (ii) operational factors, (iii) technological factors, (iv) value proposition, (v) user factors, (vi) economic factors, and (vii) environmental factors. These dimensions are composed of 31 characteristics across all FinTech business model archetypes, as shown in Table 2 . For example, D 1 (the strategic factor dimension) contains four characteristics, C 1,1 to C 1,4 , that characterize the strategic factors in more detail. Here, a strategic vision and action plan to achieve the overall goals of the FinTech venture (corporate plan) or a strategic allocation of resources to support regular business routines or the development of technological infrastructure (operational design) can be named.

As a supplement, we present definitions for all taxonomy dimensions and characteristics in Table 3 . Definitions are based on literature used for our preliminary taxonomic structure in the first iteration and have been tailored for the FinTech context.

After ending our taxonomic process, we took a more holistic view of all archetypes, SFs, and academic articles found. Using this taxonomic structure, we identified the most predominant characteristic within each dimension at the archetype level for the eight other archetypes and visualized them in Table 4 . We did not find any literature on the archetypes “financial market intermediary” and “ information extractor .” These two archetypes are, therefore, not listed in the table. To illustrate the degree of generality of the factors, i.e., scope in theory for analysis, the relative frequency distribution of the FinTech SFs is shown. Several descriptive observations and highlights can be named from our literature search results presented:

We obtained these distributions by dividing the frequency of the identified SFs per characteristic by the total data set of factors identified per the FinTech business model archetype. We then multiply the former result by 100 to obtain the relative percentage range corresponding to each characteristic (Freund et al., 2010 ). The bold black borders in Table 4 indicate the most relevant SF per FinTech business model archetype. At the same time, the gray highlighted boxes denote which characteristic is the most relevant SF per dimension according to our taxonomy-based analysis. For six of eight business model archetypes, we can observe that technological factors play an important role in their success. More precisely, “security, privacy, and transparency” have been investigated as the most relevant SF for the “co-creator of financial analysis (14%),” “cryptocurrency (10%),” “insourcer of sub-processes (9%),” and “robo-advisor (11%)” archetypes. “Technological adoption” were investigated and located as SF in the past for “alternative trading venues (10%)” and “lending communities (16%).” In the case of “lending communities,” we found that “technological adoption” was the second highest SF for a specific archetype based on our dataset. In the context of our study, we understand “technology adoption” as the competence to integrate and upgrade new or existing technologies to make innovative products and services (see Table 3 ). Likewise, the characteristics of “user trust” from the dimension of “user factors” and “technology adoption” were identified as the most relevant SF for the archetypes “payment services (11%),” and “alternative trading venues (10%)” respectively. Also, especially “information aggregators” have the operational factor of the “cost–benefit dynamic of the innovation” as a crucial SF (19%) and the highest relative frequency found. “Cost–benefit dynamic of the innovation” means a balance of the practical or economic benefit of a new product or service about its (technology) costs. To sum up, we can observe a clear tendency of most SFs to be located in the “technological factors” dimension. Furthermore, Table 4 shows that past literature provides a somewhat consensus on the SFs for “ information aggregator ” and “lending communities.” In contrast, “robo-advisors,” for example, are influenced by a more diverse set of SFs, represented through three bold black boxes

Case-based taxonomy validation and usefulness with examples from the FinTech industry and interviews

We validate and compare our taxonomy to demonstrate its usefulness and applicability with real-world examples from the FinTech industry. This case-based taxonomy validation is useful to show the ex-post applicability of identified SFs from the literature concerning real-world objects, i.e., FinTechs for each archetype (Kundisch et al., 2021 ). We identified FinTechs for each archetype within the Crunchbase database (Cruchbase, 2022a ) and used additional information from Google News about the respective FinTech concerning our identified SF. We looked for so-called Series C FinTechs, which are more established companies in later funding rounds, of around ten or more Million US$. Focusing on Series C FinTechs, we argue that FinTechs in these stages of their business life-cycle show success with their business model and underlying activities. As a result, they serve as appropriate cases and examples to compare with our identified SF in Table 4 .

Alternative trading venues

PeerStreet, an example of a successful FinTech within the “ alternative trading venues ” archetype, is a real estate crowdfunding platform founded in the USA. PeerStreet pursues the goal of providing democratic access to investments in real estate debt through advanced algorithms and big data analytics (Businesswire, 2022a , b ; Globalratings, 2022 ). For this FinTech archetype, the most important identified SF is “C 3,2 technology adoption”; hence, at the practical level, this SF is reflected in terms of the capability of PeerStreet to penetrate the market and reach a critical mass of customers by automating, simplifying, and speeding up the process of underwriting real estate loans. To achieve a profitable cash flow in the long-term, PeerStreet needs to steer its resources toward reaching a critical mass customer or expanding its customer base by targeting a larger market, enabling the company to self-finance and further scale up its business.

Co-creator of financial analysis

“C 3,3 security, privacy, and transparency” is critical for the success of FinTechs within the archetype “ co-creator of financial analysis ” (Findbiometrics, 2022 ). Biocatch is an example of a successful financial analytics Fintech, which leverages machine learning and behavioral biometrics to offer fraud protection and digital security solutions (Findbiometrics, 2022 ). The business model of Biocatch relies upon digital behavior datasets to analyze the physical and cognitive behavior of financial service users digitally. This, in turn, can lead to security, privacy, and transparency concerns among end-users concerning biometric solutions. To offset these concerns, the digital behavior databases used by Biocatch are not based on personally identifiable information, and their technological solutions are seamlessly integrated into the financial processes of financial institutions obliged to comply with privacy and security laws (The Paypers, 2022 ).

Cryptocurrency

For the FinTechs within the archetype cryptocurrency, “C 3,3 security, privacy, and transparency” was also identified as the most important SF. CoinDCX is an example of a successful crypto-trading FinTech that aims to democratize investments through cryptocurrency-based financial services (Cruchbase 2022b ). CoinDCX is India's first crypto-trading FinTech unicorn (a startup company valued at over $1 billion). CoinDCX strives to use a security-first approach to consolidate its position in the market as a differentiating factor from the competition. It seeks to become India’s most secure cryptocurrency exchange by implementing information security strategies, governance processes, and data protection programs (Livemint, 2022 ).

Information aggregator

MX Technologies, an example of a successful FinTech within the information aggregator archetype, is a data aggregation platform established in the USA. MX Technologies aggregates, analyze, and processes unstructured financial data using artificial intelligence and machine learning to leverage customer-centric banking applications and solutions (Cruchbase, 2022c ). An important SF for FinTechs belonging to the information aggregator archetype is the “C 2,4 cost–benefit dynamic of the innovation.” MX Technologies contributes to this factor by offering unique and specialized value propositions that enable its customers (e.g., financial institutions and digital banking providers) to improve their level of business intelligence. Customers are thereby enabled to make data-driven decisions based on trends in customer behavior, reduce costs derived from broken business processes, and accelerate their ability to pursue product and service innovations (Prnewswire, 2022 ). The cost–benefit dynamic of MX Technologies allows its customers to benefit from the acquisition of ready-to-use banking applications and solutions without having to make costly investments in developing such solutions in-house. At the same time, MX Technologies also benefits from lock-in effects.

Financial markets intermediary

Concerning the archetype financial markets intermediary, no relevant scientific literature has been found on the SFs of this type of FinTechs. Nonetheless, we analyze the characteristics of a German social trading FinTech named ayondo as an example of a FinTech within this archetype that, despite having maintained a run of success, ended up on the verge of failing due to regulatory changes. Although ayondo established strategic networks and alliances with top-tier banks, it aimed to be a financial services provider, targeting the end-customer market (Ayondo, 2022 ; Startupticker, 2022 ). To increase the scope of its market, ayondo opted for a competitive plan involving global branding, extending its operation to the UK (i.e., ayondo markets Ltd in London) and Asia (i.e., ayondo Ltd in Singapore). However, a FinTech company that operates in more than one country faces additional regulatory obligations due to different legal forms and restrictions. In Germany, the business model of ayondo was impacted by the enactment of new regulations in terms of privacy and security laws, such as the General Data Protection Regulation (GDPR). Furthermore, the London-based sister company was not licensed to continue business operations after the UK exit from the European Union. Because of the regulatory changes imposed by European and British regulators, ayondo suffered continuous operating losses and ultimately faced a working capital deficiency, which led to ayondo markets Ltd filing for insolvency and delisting ayondo Ltd from the Singapore Exchange (Ayondo, 2022 ; Financefeeds, 2022 ). Ayondo portfolio management GmbH has received an asset management license and strives to continue its business activities.

Information extractor

We did not find relevant literature that deals with SFs about information extractor FinTechs. However, we analyzed the characteristics of M2P Fintech as an example of a successful information extractor. M2P Fintech provides custom API platforms for banking and payment products (M2P FinTech, 2022 ). Founded in India, M2P Fintech is in a unique position and faces little to no competition in Asian countries (Techcrunch, 2022 ). The “C 1,3 competitive plan” here has played a role as an SF since M2P Fintech started and expanded in the Asian regions where competition is low for API platforms.

Insourcer of sub-processes

As an example of a successful insourcer of sub-processes, Juniper Square is a real estate investment management provider in the USA. Since “C 3,3 security, privacy and transparency” was identified as the most SF for this archetype, Juniper became very successful with SOC-2 compliance, a certification for data protection and trustworthy customer data usage. Furthermore, high-security standards, combined with the “C 4,1 convenience/usability” of the service, play an important role in the success of Juniper (Businesswire, 2022a , b ).

Lending community

“C 3,2 technology adoption” is the most important SF for FinTechs within the archetype lending community. ZestMoney is an Indian consumer lending company that connects customers with their lending partners (ZestMoney, 2022 ). Delivered through a mobile application that is supported by artificial intelligence, ZestMoney shows the competence to integrate and upgrade new or existing technologies, i.e., mobile applications with AI, to make innovative products and services for the customer (Entrepreneur, 2022 ).

Payment services

Payment services must provide a high degree of “C 5,3 User trust” to be successful. CURVE is a payment service founded in the UK. CURVE is an adequate example of a FinTech that focuses on security issues. For example, details of credit cards at CURVE are not stored on the user’s mobile device. Fraudulent behavior can thereby be avoided (Curve, 2022 ). This increases user trust and raises the tendency of the customers to use their services continuously.

Robo-advisory

For robo-advisors, we identified three SFs that play an important role in the survival of FinTechs, namely “C 3,3 security, privacy and transparency,” “C 5,4 user-perceived quality,” and “C 7,1 industry rivalry.” Albert, a successful US-based robo-advisory service, delivers automated advisory for its customers based on their preferences (Albert, 2022 ). Albert built up high privacy standards through an A-rating by the Better Business Bureau, focusing on factors like customer complaint histories. While showing no lawsuits or public scandals, Albert has been very competitive within the robo-advisor market (Americanbanker, 2022 ; Businessinsider, 2022 ).

We also discussed our findings for the usefulness of our taxonomy-based analysis with two individuals from the FinTech sector. Interview partners were located within the author’s networks and invited through e-mail. Both interviews lasted around 40 min and were held in German. They were conducted online and not recorded. Interview notes served then as primary data. We focused on evaluating our results and findings regarding usefulness and appropriateness for relevant target user groups within the FinTech ecosystem. Guidance for taxonomy evaluation proposed by Kundisch et al. ( 2021 ) was used. We interviewed one account executive from a FinTech with around 1000 employees (I1). Following the archetypes provided in this study, this FinTech offers “ payment services ” and “ information aggregator ” products. Another interview was held with a senior researcher from the FinTech sector, who is now the technical director of a start-up in the Internet of Things sector (I2). This researcher was not involved in the taxonomy development process before to be independent in his/her statements, as suggested by Kundisch et al. ( 2021 ).

Generally, both interview partners liked the content and structure of the results provided. Here, the view on different archetypes within the FinTech sector was mentioned (I1). The expert from the interviewed FinTech was somewhat able to recognize SFs from its own business, e.g., “financial capital.” As possible main target groups for this study, banks, e.g., FinTech hubs and consultants, and FinTechs in the first stage of their life-cycle are named. However, the SFs provided should be treated as supplementary information and a knowledge base for a possible reallocation of business activities (I1; I2). Stakeholders like venture capitalists are followed by their own experiences and gut feelings (also mentioned by Werth et al., ( 2019 )). Nevertheless, this target group can use it as a knowledge base. I2 marked those venture capitalists would use this information as a second-order information base within a due diligence process after the first own screening of potential FinTechs to invest in. I1 said that the dimensions provided are interesting, but FinTechs must prioritize their importance themselves. In this case, “value proposition” and “user factors” are most important, then “environmental factors” are considered. I2 also confirms this. I2 argued that the information provided in Table 4 could lead to meaningful future research on different FinTech archetypes. However, future research inquiries should consider and compare the literature on SFs of start-ups in general, e.g., team compositions, with the information provided in this study toward more detailed business model configurations.

Discussion of academic literature on success factors and real-world FinTechs per dimension

D 1 strategic factors.

Our analysis shows that the success of FinTech cloud-based or analytics-based business models (e.g., “ insourcer of sub-processes ” and “ information aggregator ”) relies to a large extent on the design of operational reliability plans to counteract shortcomings in their systems such as overflow, network, and software failures (e.g., Buyya et al., 2018 ). Alternatively, other FinTech business model archetypes such as “alternative trading venues,” “lending community,” and “robo-advisor” rely on social media marketing plans as drivers for their business models. For example, with social media marketing, FinTechs can build a digital community of supporters through digital audience-targeting strategies. Additionally, they can better shape the subjective norm prevailing in social media networks about their knowledge/awareness, perceptions, attitudes, and beliefs of the users (e.g., Clauss et al., 2020 ; Crosetto & Regner, 2018 ). This allows the FinTech business model archetypes to obtain approval, optimize campaign/service awareness, and maintain control over the communication and the disclosed information to the target digital community (Crosetto & Regner, 2018 ; Gerber & Hui, 2013 ). We see this issue, especially at M2P FinTech, which has a competitive marketing plan supported through social media activities. While social media marketing strategies may contribute further to the success of these social media-oriented FinTech archetypes, biased information and quality signals, e.g., the presence of exaggeration bias, have a detrimental effect on their potential success (Momtaz, 2020 ).

On the other hand, the FinTech business model of “ co-creator of financial analysis ” and “ payment services ” are driven by plans to build competitive intelligence as relevant strategic factors for their success. In the first case, the “ co-creator of financial analysis ” depends on the development of competitive plans based on the strategic fostering of big data analytics capabilities to provide business value to customers through the analysis of both structured and unstructured data and the automation of routine analytics functions (e.g., Mikalef et al., 2019 ; Richins et al., 2017 ). In the second case, the success of the “ payment services ” is centered on deploying competitive plans to achieve the widest possible international customer base and greater control over the network configuration (e.g., Rukanova et al., 2020 ). Nonetheless, corporate plans (e.g., strategic vision/orientation) appear less relevant for FinTech success than other strategic factors. Yet, this strategic factor can affect, for example, the perception of risk and uncertainty of FinTechs within the business model archetypes “alternative trading venues,” “co-creator of financial analysis,” “insourcer of sub-processes,” and “ payment services ” (e.g., Kauffman et al., 2018 ). In contrast, based on our case-based validation, we found that this corporate plan seems relevant for the success of the archetype “information extractor,” as identified for the FinTech M2P.

D 2 Operational factors

The success of FinTech business models with the archetypes “alternative trading venues,” “cryptocurrency,” “lending community,” and “ payment services ” depend mainly on the interplay of strategic networks and alliances to achieve network effects (e.g., Crosetto & Regner, 2018 ). These can contribute to decreasing costs of entrepreneurial effort (e.g., product/services innovations or advertising) of crowdfunding, lending, and ICO campaigns, through the establishment of a community of supporters to prompt emotional commitment and long-term interaction in the form of, e.g., information/learning exchanges, recommendations, feedback on products or services, and word-of-mouth propaganda (e.g., Kher et al., 2020 ; Schückes and Gutmann, 2020 ). Additionally, the forge of a strategic alliance with key influencers, such as renowned venture capitalists, private investors, insurers, or universities, can be used as business tools to transmit quality signals to potential investors. This offsets information asymmetries and reduces agency costs associated with sources of uncertainty such as the reputation of the FinTech entrepreneur or the nature of the FinTech product or service offering itself, among others (e.g., Kher et al., 2020 ; Momtaz, 2020 ). In the case of FinTech business models, “payment services,” the strategic alliances contributing to FinTech success mainly integrate providers’ services and constitute partnerships with banks and existing mobile banking applications. These improve the access of FinTechs to the existing payments network and enable, for example, interbank transfers (e.g., Ondrus et al., 2009 ).

In contrast, the success of “ information aggregator ” and “ insourcer of sub-processes ” FinTechs was frequently associated with the cost–benefit dynamic of the innovation . This implies that in FinTech business models with low entry barriers or with high levels of substitute competition, the realization of economic efficiency and a positive relative advantage, e.g., by a competent balance between the revenue model and transaction or switching costs are important (e.g., Thitimajshima et al., 2018 ; Trenz et al., 2013 ). As shown in the case studies section, for FinTech business models with low levels of substitute competition, it is particularly important to provide innovative and immediate responses to problems that customers would only solve on their own with high amounts of investment of time or money.

Meanwhile, for their continued success, “ co-creator of financial analysis ” FinTechs must have sufficient competency-based human resources comprising domain experts with advanced statistical knowledge, programming, analytical, and communication skills to communicate their results to non-technical executives (Liu et al., 2018 ). Also, the users of these FinTech services must possess relevant technical skills and domain knowledge to use the embedded business value (Mikalef et al., 2019 ).

D 3 Technological factors

Our analysis shows that scientific research is mostly focused on the analysis of security, privacy, and transparency, as well as the adoption of the dominant technology enabling a respective FinTech business model. Based on our analysis, the technological factors security, privacy, and transparency are relevant for the success of the FinTech business model archetypes “co-creator of financial analysis,” “cryptocurrency,” “information aggregator,” “insourcer of sub-processes,” and “robo-advisor.” Connected to the validation of “ insourcer of sub-processes ” and “robo-advisor,” we can confirm these statements. Privacy and security concerns related to the intended privacy, more specifically the transaction anonymity of blockchain-based business models, are associated with a potential risk of being used to perform illegal activities such as money laundering (e.g., Cousins et al., 2019 ). The pseudonymization of blockchain transactions is an appealing factor for using cryptocurrencies as the number of anonymity techniques increases, e.g., through centralized and decentralized mixing or ring signatures. Therefore, a better balance between privacy and the capacity to trace illegal transactions through digital forensic techniques is fundamental for the sustainable and ethical use of blockchain-based FinTechs (Cousins et al., 2019 ; Genkin et al., 2018 ). These FinTech business models also suffer security threats such as cyber-attacks, which can increase skepticism and restrain potential customers and governments. However, as shown in the case studies section, FinTechs with blockchain-based business models should turn their efforts to manage information security and privacy risks into a differentiating factor to gain a competitive advantage.

Regarding cloud-based FinTech business models (e.g., “ insourcer of sub-processes ”), in particular, the mitigation of security and control issues related to public clouds (see, e.g., Garrison et al., 2012 ) and mobile cloud storage augmentation systems (e.g., Zhou & Buyya, 2018 ) is relevant for their success. Furthermore, their aim should be to improve the privacy aspects in cloud-based applications (e.g., data confidentiality and protection) by using encryption, cloud indexing, data splitting, or secure enclaves (Buyya et al., 2018 ). For the “ information aggregator ” and “robo-advisor” FinTech business models, the level of data privacy and transparency concerning the underlying technological structures, operational processes, and pricing models are highly relevant for success (e.g., Jung et al., 2018 ; O’Reilly & Finnegan, 2010 ).

Likewise, the technology adoption factor is related to the users’ intrinsic motivations, such as ideological or philosophical motivations, e.g., the “personal enthusiasm for the business model/idea” or the “personal enthusiasm for the technology” (Fisch et al., 2019 ), is relevant for the success of the FinTech business model archetypes of “alternative trading venue” and “ lending community .” As noted in the case studies section, FinTechs targeting the end customer market must understand the knowledge of users as well as the affective and behavioral factors that form the users’ decision to adopt their technologies. Also, FinTechs targeting the end customer market must reach a critical mass of customers to achieve a sustainable cash flow in the long term. Therefore, successful “alternative trading venue” and “ lending community ” FinTechs need to understand the factors that form the customers’ perceptions, beliefs, and attitudes concerning adopting their technologies. On the other hand, the technology integration factor related to the level of integration of new technologies such as biometrics, quick response (QR) code, and near field communication (NFC) payments is especially relevant for the success of the FinTech business model archetype “ payment services ” (e.g., Ondrus et al., 2009 ; Singh & Sinha, 2020 ). Lastly, characteristics such as environmental sustainability (i.e., energy-intensive consumption) and ethical issues have an increasing impact on the sustainability of cloud and blockchain-based FinTech business models, e.g., “ cryptocurrency ” and “ insourcer of sub-processes ” (Buyya et al., 2018 ).

D 4 Value proposition

Our analysis identified the prospective value benefits of intermediation (concerning “alternative trading venues,” “information aggregator,” “lending community,” and “ payment services ”); convenience/usability (regarding “ insourcer of sub-processes ”); disintermediation (to “ cryptocurrency ”), and decision support (regarding “ co-creator of financial analysis ”) as the value propositions mostly associated with success. Especially for the archetype “insourcer of sub-processes,” we found that convenience/usability was perceived as important for the success of FinTech Zest Money. The value proposition of intermediation contributes to the success of the FinTechs as mentioned earlier. It is enabled by the creation of business value, for example, through online platforms to mediate the direct interaction and collaborative agreements of multiple affiliated or anonymous parties in terms of capital or data exchange (see, e.g., Kleinert et al., 2020 ; Koch & Siering, 2019 ; Mikalef et al., 2019 ). On the other hand, the value proposition disintermediation in FinTech furthers the success of primarily blockchain-based FinTech business models through philosophical factors, for example, increased libertarianism, the democratization of financial services, and financial inclusion.

D 5 User factors

Our analysis identified the relevant user factors that form the basis for assessment and the decision of potential users to choose the product or service offerings provided by FinTechs. User trust regarding “co-creator of financial analysis,” “cryptocurrency,” “information aggregator,” and “payment services,” given the association of the notion of trust to the perceived risks (e.g., Hong & Cha, 2013 ; Mikalef et al., 2019 ). User-perceived quality (e.g., reputation) concerning “alternative trading venue,” “information aggregator,” “insourcer of sub-processes,” and “robo-advisor” (e.g., Kleinert et al., 2020 ). User socio-economic characteristics, such as cultural or geographical similarities, regarding “ information aggregator ” and “ lending community ” (e.g., Chen et al., 2016 ); and cost attractiveness in connection with “ information aggregator ”; and ease of use , relating to “ co-creator of financial analysis ” (e.g., Thitimajshima et al., 2018 ). Our analysis shows that while user-centricity is less important than the abovementioned user factors, it is relevant for most FinTech business model archetypes, i.e., “alternative trading venue,” “insourcer of sub-processes,” “lending community,” “payment services,” and “robo-advisor” (e.g., Buyya et al., 2018 ). In contrast, our taxonomy validation identified user trust and quality as SF accelerating funding for the real-world FinTech example.

D 6 Economic factors

The identified relevant SFs include the potential for raising, lending, or investing capital beyond the traditional methods with low entry barriers (e.g., Cummings et al., 2020 ; Momtaz, 2020 ; Schückes & Gutmann, 2020 ), as well as the cost structures of FinTechs (e.g., Buyya et al., 2018 ). These provide an entrance platform for FinTech through product, service, or cost differentiation. In this context, the economic factor of financial capital is relevant for the success of the FinTech business model archetypes “alternative trading venue,” “information aggregator,” and “ lending community .” However, the cost structure is relevant for the success of “co-creator of financial analysis,” “cryptocurrency,” “insourcer of sub-processes,” “payment services,” and “robo-advisor” FinTechs. A combination of elements can enhance the potential for raising, lending, or investing venture capital through FinTechs, e.g., signal quality indicators such as prior financing success (e.g., Kleinert et al., 2020 ) or participation in accelerators programs (e.g., Ralcheva & Roosenboom, 2019 ). Conversely, high costs attributed to hardware infrastructure investments, e.g., to enhance big data analytics capabilities (e.g., Mikalef et al., 2019 ) or for cryptocurrency mining purposes, as well as high operational energy consumption due to the use of non-cost-efficient network elements like cloud systems (e.g., Buyya et al., 2018 ) can negatively affect the sustainable cost differentiation of FinTechs in relation to their competitors.

D 7 Environmental factors

The regulation was identified as a relevant SF for the FinTech business model archetypes “alternative trading venues,” “cryptocurrency,” “information aggregator,” and “ payment services ” because of its cross-cutting scope to outline and delimit their fields of application, e.g., through tax and trading conditions (e.g., Cousins et al., 2019 ; Kher et al., 2020 ). Moreover, the industry rivalry in the form of substitute products as well as new market entrants, e.g., BigTechs such as Google, Amazon, and Apple, represents a relevant SF in the “co-creator of financial analysis,” “information aggregator,” “insourcer of sub-processes,” “ lending community ”, and “ robo-advisory ” business models. We can also observe this issue for “robo-advisory,” reflected in the business activities of FinTech Albert. Furthermore, in the specific case of “information aggregator,” negative market conditions factors such as market shocks influence the success of financial e-marketplaces since these external factors can affect the price of commodities, the trading volume, and the willingness of brokers to participate in digital markets (e.g., O’Reilly & Finnegan, 2010 ).

Theoretical, methodological, and practical implications

From a theoretical view, our taxonomy of FinTech SFs contributes to the existing knowledge of FinTech by synthesizing content from 231 academic publications about potentially relevant SFs for FinTechs. The study provides a conceptual structure and terminology to SFs for FinTechs in different archetypes in the form of a taxonomic structure. Compared to the existing literature on FinTechs, we contribute to the streams of FinTech and IS literature by providing a structured content-based analysis of industry-specific SFs for different business model archetypes provided by Eickhoff et al. ( 2017 ). We identified 31 factors associated with FinTech success derived from the interdisciplinary knowledge embedded within the extant scientific literature. While these 31 factors are diverse and show a wide spread of different SFs, we identified six “grand challenges” within the FinTech ecosystem, namely “cost–benefit dynamic of the innovation,” “technology adoption,” “security, privacy, and transparency,” “user trust,” “user-perceived quality,” and “industry rivalry” that has been studied and identified by the past researchers. These “grand challenges” within the ecosystem are visualized in Fig.  4 and are arranged with their associated dimension:

“Grand Challenges” within the FinTech ecosystem as identified by the taxonomy-based analysis

While FinTechs are “technology-driven” (e.g., Gomber et al., 2018 ), it is not surprising that our examination reveals technological factors as crucial for the success of six of the eight archetypes. However, this uniqueness of technological factors is not a necessary condition for success. As identified by our examination, e.g., within the archetype of “ robo-advisory ” and past taxonomic approaches in the FinTech sector (Drasch et al., 2018 ; Gimpel et al., 2018 ), success remains a composition and configuration of many factors that can potentially be relevant for FinTech survival. Our examination shows that while FinTech companies can take internal actions to respond to the “grand challenges” strategically, the impact of external effects such as regulation can counteract these efforts and influence the survival and growth of some FinTech business models in countries with restrictive legal and regulatory systems, such as within the European Union.

However, our study and the results derived can explain the differences and similarities between SFs as a first step, uncover knowledge gaps that have been overlooked and not studied so far (e.g., Gazel & Schwienbacher, 2020 ; Soto-Simeone et al. 2020 ). While our review shows that these factors were researched extensively, our study can serve as an ignition for more tailored research and examinations of other factors potentially relevant to the success of FinTechs. Besides the empirical derivation of SFs within the FinTech area, we illustrate the degree of generality of these characteristics and provide insights on their effect on diverse FinTech business model archetypes at seven distinct dimensions of success, thereby addressing a future research direction pointed out by Eickhoff et al. ( 2017 ). We validate these identified factors by comparing and discussing them in the context of successful real-world FinTech companies. In addition, we evaluated the usefulness of our findings with two individuals from the FinTech ecosystem. The participants that were interviewed confirmed the SFs identified as relevant and comprehensive.

From a methodological standpoint, we combine the taxonomic approach by Nickerson et al. ( 2013 ) with content analysis as a technique to identify SFs. In this manner, the taxonomic approach guided our systematic classification of SFs, and the content analysis methodically allowed us to identify relevant dimensions and characteristics. With this structured approach, we could review and abstract the findings of the extant scientific literature more effectively and provide an overview of how the identified SFs have been studied so far in the academic literature. We transfer our findings from the review process to real-world cases from the FinTech sector, showing the appropriateness of some SFs within a market context. Therefore, case-based taxonomy validation was useful to show how to transfer findings from past literature provided by taxonomies to real-world cases and practical settings.

From the practitioner’s perspective, potential founders and stakeholders of FinTechs can use our taxonomy to obtain a holistic overview of the relevant factors that contribute to the success of each FinTech business model archetype. Furthermore, interested practitioners can find and deviate a prioritization of possibly relevant SFs that maintain the survival of their own venture. Likewise, already-founded FinTechs can assess and refine their business activities and current capabilities based on our identified SFs to detect potential shortcomings in their business logic and value networks to achieve competitive business models. Additionally, our taxonomy can serve as a discussion platform and supplementary knowledge base for members of the financial ecosystem, e.g., banks, FinTech hubs, consultants, or venture capitalists, to identify the possibly relevant SFs across distinct business model archetypes in the FinTech ecosystem.

Limitations and future research directions

Although our study is based on the widely accepted frameworks and procedures of Nickerson et al. ( 2013 ) and Webster and Watson ( 2002 ), the criteria applied during the literature review may impact the comprehensiveness of the results. This is especially the case for the business model archetypes of robo-advisors ( n  = 4 ) and information aggregators ( n  = 3). Results for these archetypes are based on a small sample of identified papers and a real-world example. Therefore, this study’s inferences should be treated carefully in light of this limitation. Among these criteria is the time restriction to include only scientific articles published from 2008 onward and the inclusion of only scientific articles published in leading peer-reviewed academic business research journals and conference proceedings. Additionally, potential limitations related to the taxonomic approach must be considered. For example, it is impossible to affirm completeness in the case of all relevant SFs of FinTech since we examined the literature within our inclusion criteria and stopped the empirical analysis after all adopted taxonomic objective and subjective ending conditions were met. Furthermore, the definition of meta-characteristic or ending conditions in taxonomy development frameworks is part of a subjective process based on value judgments made by the authors (Nickerson et al., 2013 ).

We encourage researchers interested in FinTech, especially in FinTech success, to build on our findings that leave room for future research. Although the original goal of a taxonomy is not to build theory or to identify, for example, causal relationships between its composing objects, the integrative knowledge resulting from this analysis can be used in future research to discern relationships between the identified SFs at different levels or be used to support theory building processes, also mentioned by Kundisch et al. ( 2021 ).

Further research can also build on our insights and enrich our taxonomy of FinTech SFs with causal explanations or testable propositions (Gregor, 2006 ; Muntermann et al., 2015 ) to assess the level of success criticality of the identified SFs either through different (i) FinTech lifecycle stages; (ii) archetype-specific product or service lifecycles; or (iii) in regards to diverse exploration–exploitation (corporate, productivity, competitive or marketing) strategies to gain a better understanding of the interconnection between strategic entrepreneurship and FinTech success. By providing a justified list of SFs and multi-dimensional conceptualization of FinTech success, this study also provides the basis for the development of strategic analysis tools, e.g., segment-based CPMs, to analyze the particular competitive position, strengths, and weaknesses of a FinTech company within the industry (e.g., David & David, 2017 ). We also validate our findings with (short) success stories with real-world examples from the FinTech sector to show important highlights from our results. Besides the archetypes “ insourcer of sub-processes ” and “robo-advisor,” we only focus on and discuss one SF. Consequentially, these cases are not complete assessments of the whole business model. A more detailed analysis of the configurations and SFs of FinTech business models in light of our results can be an avenue for future research. Our analysis is focused on FinTech SFs. Therefore, the cases contain FinTechs, that were able to show success with their business model and underlying activities. However, examining the success/failure dichotomy also constitutes an important supplementary line of research to be explored. While success and failure factors have no mutually opposing effects as a matter of principle (Dwivedi et al., 2015 ; Williams & Ramaprasad, 1996 ), the identification of relevant failure factors, their direct/indirect effects, and an investigation of failed FinTechs are important to avoid diverting into an incomplete strategic planning perspective, i.e., “complementarities trap” (Pettigrew et al., 2003 ).

Furthermore, in line with our research goal, we chose a conceptual-to-empirical approach as a starting point for our taxonomic process. However, a future alternative taxonomy can emerge from an empirical-to-conceptual approach to obtain a different perspective, e.g., by conducting expert interviews or focus groups with practitioners in the financial ecosystem. A comparison of both taxonomies contributes to identifying existent research-to-practice gaps. Also, because we choose one FinTech per archetype to reflect and validate our results from taxonomy, further research can choose a more comprehensive way of discussing real-world examples from the FinTech industry with the results presented.

Conclusions

In this study, we provide insights into the potential determinants of FinTech success through a taxonomy-based analysis of 231 research articles built on empirically validated FinTech business model archetypes. Our analysis shows that technological characteristics such as “security, privacy, and transparency” and “technology adoption,” along with user factors such as “user trust” and “user-perceived quality” and operational factors as the “cost–benefit dynamic of the innovation” are relevant for FinTech success. At a more specific archetypal level, we identified (i) “security, privacy, and transparency” as the most relevant SF for the “cryptocurrency,” “co-creator of financial analysis,” “ insourcer of sub-processes ”, and “robo-advisor” archetypes; (ii) “technology adoption” as the most relevant SF for the FinTech business model archetypes of “alternative trading venue” and “ lending community ”; and (iii) the “user trust,” “user-perceived quality”, and “cost–benefit dynamic of the innovation” as the most relevant factors for the success of the FinTech business model archetypes “payment services,” “robo-advisor,” and “information aggregator,” respectively. Furthermore, we validate and discuss our identified factors with examples from the FinTech industry. Also, we evaluated the usefulness of our findings with two individuals from the FinTech ecosystem. Compared to previous literature, we contribute to the need within the streams of FinTech and IS literature by providing a structured content-based analysis of industry-specific SFs for FinTechs that can explain the differences and similarities between them and uncover knowledge gaps (e.g., Gazel & Schwienbacher, 2020 ; Soto-Simeone et al. 2020 ). As a result, the taxonomy can be used to solve practical problems, i.e., identifying potentially relevant SFs for FinTechs. The insights gained in this study suggest that the SFs play an important role in the success of FinTechs and should therefore be treated as a priority for the sustainable development of FinTech business models.

Data Availability

(Anonymized) data and analysis that support the findings of this study are available on request by the corresponding author.

Ain, N., Vaia, G., DeLone, W. H., & Waheed, M. (2019). Two decades of research on business intelligence system adoption, utilization and success—A systematic literature review. Decision Support Systems, 125 , 113113. https://doi.org/10.1016/j.dss.2019.113113

Article   Google Scholar  

Albert (2022). About us. Retrieved March 11, 2023, from https://albert.com/about/

Al-Debei, M. M., & Avison, D. (2010). Developing a unified framework of the business model concept. European Journal of Information Systems, 19 (3), 359–376. https://doi.org/10.1057/ejis.2010.21

Alt, R., & Zimmermann, H. D. (2001). Introduction to special section—Business models. Electronic Markets, 11 (1), 1–9. https://doi.org/10.1080/713765630

Americanbanker (2022). Personal finance Fintech Albert rolls out checking account, Retrieved March 11, 2023, from https://www.americanbanker.com/news/personal-financeFintech-albert-rolls-out-checking-account

Arner, D., Barberis, J., & Buckley, R. P. (2016). 150 years of Fintech: An evolutionary analysis. The Finsia Journal of Applied Finance, 3 (3), 22–29.  https://search.informit.org/doi/10.3316/ielapa.419780653701585

Google Scholar  

Ayondo (2022). Ayondo—A strong brand for a unique business model, made in Germany. Retrieved March 11, 2023, from https://ayondo.com/en/history

Beinke, J. H., Nguyen, D., & Teuteberg, F. (2018). Towards a business model taxonomy of startups in the finance sector using blockchain. In Proceedings of the 39th International Conference on Information Systems (ICIS) .

Bhattacharjee, D. (2015). Competitive profile matrix: A theoretical review. ABAC Journal, 35 (2), 61–70.

Böhm, M., Weking, J., Fortunat, F., Müller, S., Welpe, I., & Krcmar, H. (2017). The business model DNA: Towards an approach for predicting business model success. In Proceedings of the 13th International Conference on Wirtschaftsinformatik (WI) .

Buckley, R. P., & Webster, S. (2016). Fintech in developing countries: Charting new customer journeys. Journal of Financial Transformation, 44 , 1–19 Available at SSRN: https://ssrn.com/abstract=2850091

Businessinsider. (2022). Is Albert trustworthy? Retrieved March 11, 2023, from https://www.businessinsider.com/personal-finance/albert-investing-review#is-albert-trustworthy ?

Businesswire. (2022a). PeerStreet launches a secondary marketplace to increase liquidity for investors. Retrieved March 11, 2023, from https://www.businesswire.com/news/home/20211102005753/en/PeerStreet-Launches-a-Secondary-Marketplace-to-Increase-Liquidity-for-Investors

Businesswire. (2022b). CrowdStreet and Juniper Square Partner to usher in the next chapter of digital transformation for the commercial real estate industry. Retrieved March 11, 2023, from https://www.businesswire.com/news/home/20210921005867/en/CrowdStreet-and-Juniper-Square-Partner-to-Usher-in-the-Next-Chapter-of-Digital-Transformation-forthe-Commercial-Real-Estate-Industry

Buyya, R., Netto, M. A. S., Toosi, A. N., Rodriguez, M. A., & Toosi, A. N. (2018). A manifesto for future generation cloud computing. ACM Computing Surveys, 51 (5), 1–38. https://doi.org/10.1145/3241737

Chen, X., Jin, F., Zhang, Q., & Yang, L. (2016). Are investors rational or perceptual in P2P lending? Information Systems and E-Business Management, 14 (4), 921–944. https://doi.org/10.1007/s10257-016-0305-z

Chesbrough, H., & Rosenbloom, R. S. (2002). The role of the business model in capturing value from innovation: Evidence from Xerox corporation’s technology spin-off companies. Industrial and Corporate Change, 11 (3), 529–555. https://doi.org/10.1093/icc/11.3.529

Clauss, T., Niemand, T., Kraus, S., Schnetzer, P., & Brem, A. (2020). Increasing crowdfunding success through social media: The importance of reach and utilisation in rewardbased crowdfunding. International Journal of Innovation Management, 24 (3), 1–30. https://doi.org/10.1142/S1363919620500267

Cousins, K., Subramanian, H., & Esmaeilzadeh, P. (2019). A value-sensitive design perspective of cryptocurrencies: A research agenda. Communications of the Association for Information Systems, 45 , 511–547. https://doi.org/10.17705/1CAIS.04527

Crosetto, P., & Regner, T. (2018). It’s never too late: Funding dynamics and self pledges in reward-based crowdfunding. Research Policy, 47 (8), 1463–1477. https://doi.org/10.1016/j.respol.2018.04.020

Cruchbase. (2022a). Crunchbase database. Retrieved March 11, 2023, from https://www.crunchbase.com/

Cruchbase. (2022b). CoinDCX, Retrieved March 11, 2023, from https://www.crunchbase.com/organization/coindcx

Cruchbase. (2022c). Moneydesktop, Retrieved March 11, 2023, from https://www.crunchbase.com/organization/moneydesktop

Cummings, M. E., Rawhouser, H., Vismara, S., & Hamilton, E. L. (2020). An equity crowdfunding research agenda: Evidence from stakeholder participation in the rulemaking process. Small Business Economics, 54 (4), 907–932. https://doi.org/10.1007/s11187-018-00134-5

Curve (2022). How it works. Retrieved March 11, 2023, from https://www.curve.com/how-it-works/

Cziesla, T. (2015). A literature review on digital transformation in the financial service industry. In Proceedings of the 28th Bled Conference . Slovenia.

David, F. R., & David, F. R. (2017). Strategic management—Concepts and cases: A competitive advantage approach ((16th ed.). ed.). Pearson.

DeLone, W. H., & McLean, E. R. (2003). The Delone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19 (4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

Demir, A., Pesqué-Cela, V., Altunbas, Y., & Murinde, V. (2020). Fintech, Financial inclusion and income inequality: A quantile regression approach. The European Journal of Finance , 1–22. https://doi.org/10.1080/1351847X.2020.1772335

Drasch, B. J., Schweizer, A., & Urbach, N. (2018). Integrating the “troublemakers”: A taxonomy for cooperation between banks and Fintechs. Journal of Economics and Business, 100 , 26–42. https://doi.org/10.1016/j.jeconbus.2018.04.002

Dratva, R. (2020). Is open banking driving the financial industry towards a true electronic market? Electronic Markets, 30 (1), 1–3. https://doi.org/10.1007/s12525-020-00403-w

Dwivedi, Y. K., Wastell, D., Laumer, S., Henriksen, H. Z., Myers, M. D., Bunker, D., & Srivastava, S. C. (2015). Research on information systems failures and successes: Status update and future directions. Information Systems Frontiers, 17 (1), 143–157. https://doi.org/10.1007/s10796-014-9500-y

Eickhoff, M., Muntermann, J., & Weinrich, T. (2017). What do Fintechs actually do? A taxonomy of Fintech business models. In Proceedings of the 38th International Conference on Information Systems (ICIS) . South Korea.

Entrepreneur. (2022). The rise of buy now pay later. Retrieved March 11, 2023, from https://www.entrepreneur.com/article/384524

Financefeeds. (2022) Ayondo must make exit offer, Appeals SGX delisting notice. Retrieved March 11, 2023, from https://financefeeds.com/ayondo-must-make-exit-offer-appealssgx-delisting-notice/

Findbiometrics. (2022). BioCatch named to CB insights Fintech 250. Retrieved March 11, 2023, from https://findbiometrics.com/biocatch-named-cb-insights-Fintech-250-091701/

Fintech Magazine. (2022). Struggling to scale? Fintech decacorns and the downturn. Retrieved March 11, 2023, from https://fintechmagazine.com/banking/struggling-to-scalefintech-decacorns-and-the-downturn

Fisch, C., Masiak, C., Vismara, S., & Block, J. (2019). Motives and profiles of ICO investors. Journal of Business Research, 125 , 564–576. https://doi.org/10.1016/j.jbusres.2019.07.036

Freund, Y. P. (1988). Critical success factors. Planning Review, 16 (4), 20–23. https://doi.org/10.1108/eb054225

Freund, R. J., Mohr, D., & Wilson, W. J. (2010). Statistical methods (3rd ed.). Academic Press.

Garrison, G., Kim, S., & Wakefield, R. L. (2012). Success factors for deploying cloud computing. Communications of the ACM, 55 (9), 62–68. https://doi.org/10.1145/2330667.2330685

Gazel, M., & Schwienbacher, A. (2020). Entrepreneurial Fintech clusters. Small Business Economics, 57 , 883–903. https://doi.org/10.1007/s11187-020-00331-1

Genkin, D., Papadopoulos, D., & Papamanthou, C. (2018). Privacy in decentralized cryptocurrencies. Communications of the ACM, 61 (6), 78–88. https://doi.org/10.1145/3132696

Gerber, E. M., & Hui, J. (2013). Crowdfunding: Motivations and deterrents for participation. ACM Transactions on Computer-Human Interaction, 20 (6), 1–32. https://doi.org/10.1145/2530540

Gimpel, H., Rau, D., & Röglinger, M. (2018). Understanding Fintech start-ups—A taxonomy of consumer-oriented service offerings. Electronic Markets, 28 (3), 245–264. https://doi.org/10.1007/s12525-017-0275-0

Globalratings (2022) PeerStreet review 2021: Investing in real estate loans, Retrieved March 11, 2023, from https://www.gobankingrates.com/reviews/peerstreet/

Gomber, P., Koch, J. A., & Siering, M. (2017). Digital finance and Fintech: Current research and future research directions. Journal of Business Economics, 87 (5), 537–580. https://doi.org/10.1007/s11573-017-0852-x

Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2018). On the Fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35 (1), 220–265. https://doi.org/10.1080/07421222.2018.1440766

Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30 (3), 611–642. https://doi.org/10.2307/25148742

Groenewegen, G., & de Langen, F. (2012). Critical success factors of the survival of start-ups with a radical innovation. Journal of Applied Economics and Business Research, 2 (3), 155–171.

Hedman, J., & Kalling, T. (2003). The business model concept: Theoretical underpinnings and empirical illustrations. European Journal of Information Systems, 12 (1), 49–59. https://doi.org/10.1057/palgrave.ejis.3000446

Hennig-Thurau, T., Sattler, H., Dyckhoff, H., Franke, N., & Schreyögg, G. (2022). VHB-JOURQUAL3. Retrieved March 11, 2023, from https://www.vhbonline.org/vhb4you/vhbjourqual/vhb-jourqual-3/gesamtliste

Hinde, S., & Spackman, E. (2015). Bidirectional citation searching to completion: An exploration of literature searching methods. PharmacoEconomics, 33 (1), 5–11. https://doi.org/10.1007/s40273-014-0205-3

Hong, I. B., & Cha, H. S. (2013). The mediating role of consumer trust in an online merchant in predicting purchase intention. International Journal of Information Management, 33 (6), 927–939. https://doi.org/10.1016/j.ijinfomgt.2013.08.007

Imerman, M. B., & Fabozzi, F. J. (2020). Cashing in on innovation: A taxonomy of Fintech. Journal of Asset Management, 21 , 167–177. https://doi.org/10.1057/s41260-020-00163-4

Insider Intelligence (2021). US consumer Fintech adoption reaches 88%, Retrieved March 11, 2023, from https://www.insiderintelligence.com/content/us-consumer-Fintechadoption-surges

Jung, D., Dorner, V., Weinhardt, C., & Pusmaz, H. (2018). Designing a robo-advisor for risk-averse, low-budget consumers. Electronic Markets, 28 (3), 367–380. https://doi.org/10.1007/s12525-017-0279-9

Kauffman, R. J., Ma, D., & Yu, M. (2018). A metrics suite of cloud computing adoption readiness. Electronic Markets, 28 (1), 11–37. https://doi.org/10.1007/s12525-015-0213-y

Kher, R., Terjesen, S., & Liu, C. (2020). Blockchain, bitcoin, and ICOs: A review and research agenda. Small Business Economics, 56 , 1699–1720. https://doi.org/10.1007/s11187-019-00286-y

Klein, J., Stuckenborg, L., & Leker, J. (2020). Hot or not–Which features make Fintechs attractive for investors? The Journal of Entrepreneurial. Finance, 22 (1), 27–60. https://doi.org/10.57229/2373-1761.1372

Kleinert, S., Volkmann, C., & Grünhagen, M. (2020). Third-party signals in equity crowdfunding: The role of prior financing. Small Business Economics, 54 (1), 341–365. https://doi.org/10.1007/s11187-018-0125-2

Koch, J., & Siering, M. (2019). The recipe of successful crowdfunding campaigns. Electronic Markets, 29 (4), 661–679. https://doi.org/10.1007/s12525-019-00357-8

Kolokas, D., Vanacker, T., Veredas, D., & Zahra, S. A. (2022). Venture capital, credit, and Fintech start-up formation: A cross-country study. Entrepreneurship Theory and Practice, 46 (5), 1198–1230. https://doi.org/10.1177/1042258720972652

Kundisch, D., Muntermann, J., Oberländer, A. M., Rau, D., Röglinger, M., Schoormann, T., & Szopinski, D. (2021). An update for taxonomy designers. Business & Information Systems Engineering, 64 , 421–439. https://doi.org/10.1007/s12599-021-00723-x

Lagna, A., & Ravishankar, M. N. (2021). Making the world a better place with Fintech research. Information Systems Journal, 32 (1), 61–102. https://doi.org/10.1111/isj.12333

Laidroo, L., & Avarmaa, M. (2020). The role of location in Fintech formation. ENtrepreneurship & Regional Development, 32 (7–8), 555–572. https://doi.org/10.1080/08985626.2019.1675777

Liu, Y., Han, H., & DeBello, J. (2018). The challenges of business analytics: Successes and failures. In Proceedings of the 51st Hawaii International Conference on System Sciences (HICSS) .

Livemint (2022). CoinDCX appoints Divakar Prayaga as head of information security, Retrieved March 11, 2023, from https://www.livemint.com/companies/news/coindcxappoints-divakar-prayaga-as-head-of-information-security-11641987879184.html

M2P Fintech. (2022). About us. Retrieved March 11, 2023, from https://m2pFintech.com/about-us/

Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2019). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information & Management, 57 (2), 103–169. https://doi.org/10.1016/j.im.2019.05.004

Momtaz, P. P. (2020). Entrepreneurial finance and moral hazard: Evidence from token offerings. Journal of Business Venturing, 36 (1), 106001. https://doi.org/10.1016/j.jbusvent.2020.106001

Mumtaz, M. Z., & Smith, Z. A. (2020). Empirical examination of the role of Fintech in monetary policy. Pacific Economic Review, 25 (5), 620–640. https://doi.org/10.1111/1468-0106.12319

Muntermann, J., Nickerson, R., & Varshney, U. (2015). Towards the development of a taxonomic theory. In Proceedings of the 21st Americas Conference on Information Systems (AMCIS) .

Nagel, E., Kranz, J., Sandner, P., & Hopf, S. (2019). How blockchain facilitates smart city applications—Development of a multi-layer taxonomy. In Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm-Uppsala, Sweden .

Nickerson, R. C., Varshney, U., & Muntermann, J. (2013). A method for taxonomy development and its application in information systems. European Journal of Information Systems, 22 (3), 336–359. https://doi.org/10.1057/ejis.2012.26

Nicoletti, B. (2017). Critical success factors. In B. Nicoletti (Ed.), The Future of Fintech (pp. 161–175). Palgrave Macmillan.

O’Reilly, P., & Finnegan, P. (2010). Intermediaries in inter-organisational networks: Building a theory of electronic marketplace performance. European Journal of Information Systems, 19 (4), 462–480. https://doi.org/10.1057/ejis.2010.12

Omarova, S. T. (2019). New tech v. new deal: Fintech as a systemic phenomenon. Yale Journal on Regulation, 36 , 735–793.

Ondrus, J., Lyytinen, K., & Pigneur, Y. (2009). Why mobile payments fail? Towards a dynamic and multi-perspective explanation. Proceedings of the 42nd Hawaii International Conference on System Sciences (HICSS).   https://doi.org/10.1109/HICSS.2009.510

Chapter   Google Scholar  

Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers . John Wiley & Sons.

Osterwalder, A., Pigneur, Y., & Tucci, C. L. (2005). Clarifying business models: Origins, present, and future of the concept. Communications of the Association for Information Systems, 16 (1), 1–25. https://doi.org/10.17705/1CAIS.01601

Oxford Dictionaries (2022). Definition of Fintech, critical, success and factor in English, Retrieved March 11, 2023, from https://www.lexico.com/definition/Fintech.../critical.../success.../factor

Petter, S., DeLone, W., & McLean, E. R. (2013). Information systems success: The quest for the independent variables. Journal of Management Information Systems, 29 (4), 7–62. https://doi.org/10.2753/MIS0742-1222290401

Pettigrew, A. M., Whittington, R., Melin, L., Sanchez-Runde, C., Van den Bosch, F. A., Ruigrok, W., & Numagami, T. (2003). Innovative forms of organizing: International perspectives . Sage.

Book   Google Scholar  

Prnewswire (2022). MX helps OrbisPay users get wages faster, Retrieved March 11, 2023, from https://www.prnewswire.com/news-releases/mx-helps-orbispay-users-get-wagesfaster-301377362.html

Ralcheva, A., & Roosenboom, P. (2019). Forecasting success in equity crowdfunding. Small Business Economics, 55 (1), 1–18. https://doi.org/10.1007/s11187-019-00144-x

Richins, G., Stapleton, A., Stratopoulos, T. C., & Wong, C. (2017). Big data analytics: Opportunity or threat for the accounting profession? Journal of Information Systems, 31 (3), 63–79. https://doi.org/10.2308/isys-51805

Rockart, J. (1979). Chief executives define their own information needs. Harvard Business Review, 57 (2), 81–92.

Rukanova, B., de Reuver, M., Henningsson, S., Nikayin, F., & Tan, Y. H. (2020). Emergence of collective digital innovations through the process of control point driven network reconfiguration and reframing: The case of mobile payment. Electronic Markets, 30 (1), 107–129. https://doi.org/10.1007/s12525-019-00352-z

Santisteban, J., & Mauricio, D. (2017). Systematic literature review of critical success factors of information technology startups. Academy of Entrepreneurship Journal, 23 (2), 1–23.

Schückes, M., & Gutmann, T. (2020). Why do startups pursue initial coin offerings (ICOs)? The role of economic drivers and social identity on funding choice. Small Business Economics, 57 , 1027–1052. https://doi.org/10.1007/s11187-020-00337-9

Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant’s intention to use a mobile wallet technology. Journal of Retailing and Consumer Services, 52 , 101894. https://doi.org/10.1016/j.jretconser.2019.101894

Soto-Simeone, A., Sirén, C., & Antretter, T. (2020). New venture survival: A review and extension. International Journal of Management Reviews, 22 (4), 378–407. https://doi.org/10.1111/ijmr.12229

Startupticker. (2022). Ayondo enters into media partnership with SevenVentures. Retrieved March 11, 2023, from https://www.startupticker.ch/en/news/ayondo-schliesstmediapartnerschaft-mit-sevenventures

Statista. (2021a) Number of Fintech startups worldwide from 2018 to November 2021a, by region. Retrieved March 11, 2023, from https://www.statista.com/statistics/893954/number-Fintech-startups-by-region/

Statista (2021b) Total value of investments into Fintech companies worldwide from 2010 to 1st half 2021b (in billion U.S. Dollars), Retrieved March 11, 2023, from https://www.statista.com/statistics/719385/investments-into-Fintech-companies-globally/

Stuckenborg, L., & Leker, J. (2019). The survival of the German Fintech market: An accounting-based valuation. The Journal of Entrepreneurial. Finance, 21 (1), 57–92. https://doi.org/10.57229/2373-1761.1334

Sturm, B., & Sunyaev, A. (2017). You can’t make bricks without straw: Designing systematic literature search systems. In Proceedings of the 38th International Conference on Information Systems (ICIS) .

Szopinski, D., Schoormann, T., & Kundisch, D. (2019). Because your taxonomy is worth it: Towards a framework for taxonomy evaluation. In Proceedings of the 27th European Conference on Information Systems (ECIS) .

Techcrunch. (2022). Payments infra startup M2P Fintech valued at over $600 million in $56 million funding, Retrieved March 11, 2023, from https://techcrunch.com/2022/01/19/m2p-Fintech-funding-insight-partners/?guccounter=1&guce_referrer=aHR0cHM6Ly9uZXdzLmdvb2dsZS5jb20v&guce_referrer_sig=AQAAABRIXYG_jmLDlwZlmQx6N0J29TIYkAw4gawNaFb20BHvM3nY9gK8HHFTWWh4HEltcRCmQ33kNyY028EXAx5oyLIn5dgaGR95LNNxMptoBCjjwkTyCHUUnmSYvo782__MtnskFUNuWIak2RKMKvxvQq5B4-sIcLZSTIzvz8ndL9Q

Teece, D. J. (2010). Business models, business strategy and innovation. Long Range Planning, 43 (2), 172–194. https://doi.org/10.1016/j.lrp.2009.07.003

The Fintech Mag (2022). Why Fintech startups fail? 75% of VC backed Fintech startups crash. Let’s see why. Retrieved March 11, 2023, from https://theFintechmag.com/whyFintech-startups-fail/

The Paypers (2022). Fighting fraud with behavioural biometrics—Exclusive interview with BioCatch. Retrieved March 11, 2023, from https://thepaypers.com/interviews/fightingfraud-with-behavioural-biometrics-exclusive-interview-with-biocatch/772570-38

Thitimajshima, W., Esichaikul, V., & Krairit, D. (2018). A framework to identify factors affecting the performance of third-party B2B e-marketplaces: A seller’s perspective. Electronic Markets, 28 (2), 129–147. https://doi.org/10.1007/s12525-017-0256-3

Thompson, A., Peteraf, M., Gamble, J., & Strickland, A. (2018). Crafting and executing strategy: The quest for competitive advantage: Concepts and cases (21st ed.). McGraw-Hill Education.

Trenz, M., Huntgeburth, J. C., & Veit, D. J. (2013a). The role of uncertainty in cloud computing continuance: Antecedents, mitigators and consequences. In Proceedings of the 21 st European Conference on Information Systems (ECIS) . Netherland.

Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a review. MIS Quarterly, 26 (2), 13–23.

Weking, J., Böttcher, T., Hermes, S., & Hein, A. (2019). Does business model matter for startup success? A quantitative analysis. In Proceedings of the 27th European Conference on Information Systems (ECIS) . Sweden.

Werth, O., Rodríguez Cardona, D., Nowatschin, J., Werner, M., Guhr, N., & Breitner, M. H. (2019). Challenges of the financial industry—An analysis of critical success factors for Fintechs. In Proceedings of the 25th Americas Conference on Information Systems (AMCIS) .

Williams, J. J., & Ramaprasad, A. (1996). A taxonomy of critical success factors. European Journal of Information Systems, 5 (4), 250–260. https://doi.org/10.1057/ejis.1996.30

Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (EASE).   https://doi.org/10.1145/2601248.2601268

Zestmoney (2022). About us. Retrieved March 11, 2023. https://www.zestmoney.in/about

Zhou, B., & Buyya, R. (2018). Augmentation techniques for mobile cloud computing: A taxonomy, survey, and future directions. ACM Computing Surveys, 51 (1), 1–38. https://doi.org/10.1145/3152397

Zott, C., Amit, R., & Massa, L. (2011). The business model: Recent developments and future research. Journal of Management, 37 (4), 1019–1042. https://doi.org/10.1177/0149206311406265

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Acknowledgements

First, we would like to thank the responsible editor, Ulrike E. Lechner, for her suggestions for improvement and believing in this paper. Also, the authors would like to thank the anonymous reviewers for the valuable comments and careful reviews during the revision process. We would also like to thank the interview partners for evaluating our findings as well as our colleagues for many fruitful discussions.

Open Access funding enabled and organized by Projekt DEAL. This research was partly funded by the Lower Saxony Ministry for Science and Culture and Volkswagen Foundation within the PhD program “Design of Mobile Information Systems in the Digital Transformation” under the project number 21-78904-63-9/16.

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Oliver Werth

Information Systems Institute, Leibniz University Hannover, Königsworther Platz 1, 30167, Hanover, Germany

Davinia Rodríguez Cardona & Michael H. Breitner

Faculty of Business and Economics, Chair of Electronic Finance and Digital Markets, Georg-August-Universität Göttingen, Platz Der Göttinger Sieben 5, Göttingen, 37073, Germany

Albert Torno

Faculty of Business and Economics, Chair of Financial Data Analytics, Augsburg University, Universitätsstrasse 16, 86159, Augsburg, Germany

Jan Muntermann

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Correspondence to Oliver Werth .

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Werth, O., Cardona, D.R., Torno, A. et al. What determines FinTech success?—A taxonomy-based analysis of FinTech success factors. Electron Markets 33 , 21 (2023). https://doi.org/10.1007/s12525-023-00626-7

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Published : 19 May 2023

DOI : https://doi.org/10.1007/s12525-023-00626-7

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How Kingsley Gate Helped a Major FinTech Player Hire a Region-Wide Head of Sales in 87 days

Identifying the business problem, kingsley gate’s tailored approach.

A multinational fintech company, committed to revolutionizing the ever-evolving world of commerce, decided to disrupt their presence in Latin America (LATAM).

The reason? LATAM has been experiencing a boom, driven by rising internet penetration, mobile adoption, and a growing appetite for digital financial services. However, attracting top-tier executive talent for regional leadership roles in this dynamic market presents its own set of unique challenges.

This case study details our successful approach to filling a Head of Sales position within the competitive landscape in an 87-day timeframe.

Kingsley Gate’s research of the emerging fintech landscape in LATAM revealed a key insight: many multinational companies with a presence in LATAM lack established regional headquarters in key markets like Brazil due to high cost. Instead, they often set up hubs in Mexico, Argentina, Colombia, or Chile.

This results in fewer executives having exposure to multi-country operations. The geographic distribution creates a talent pool with limited exposure to cross-border operations and a regional strategic viewpoint. Local executives may excel in their domestic markets but struggle to translate that success into a broader regional vision.

Additionally, their network of relationships might be primarily concentrated within their home country, hindering their ability to leverage regional partnerships and opportunities. Lastly, the local executives bring limited knowledge of market dynamics externally and lack awareness of potential BD opportunities.

All the above factors can significantly impede a company’s ability to capitalize on the full potential of the region’s commerce landscape.

To navigate this complex landscape and identify the best possible candidates, we implemented a multi-pronged approach:

Target Focus

• Market Specificity: We focused on industries directly involved in the payments ecosystem, including acquirers, merchants, and payments-oriented SaaS/Digital companies. This ensured that potential candidates possessed a deep understanding of the specific challenges and opportunities within the sector.
• Executive Focus: Our search targeted high-level decision makers with a proven track record of success. This included CEOs, GMs, Executive Directors, and multi-country and in-country Heads of Sales. By focusing on leadership roles, we aimed to identify individuals who could provide strategic vision and direction while also possessing the operational expertise to drive results.

Deep Market Knowledge

We recognized the competitive nature of the market and adjusted our outreach strategies accordingly.

• Understanding Career Mobility: We acknowledged the frequent career changes and proactively targeted executives who might not be actively searching but were open to new opportunities that aligned with their career goals.
• Mapping the Startup Ecosystem: We identified rising stars within the burgeoning payments startup and fintech scene, recognizing their potential to disrupt the established players.
• Competitive Intelligence: We understood the tactics of competitor approaches and employed alternative engagement strategies to break through the noise and capture candidate interest.

Rigorous Screening Process

While a competitive market offered a large pool of candidates, not all were the right fit. We implemented a robust screening process to identify individuals who possessed the following critical attributes:

• Strategic Business Leadership: We sought candidates with a proven ability to develop and execute a regional growth strategy. This required a deep understanding of market dynamics, competitor analysis, and the ability to translate strategic vision into actionable plans.
• Regional Exposure: Having a strong track record of success in multiple LATAM markets was crucial. This ensured the candidate could navigate the complexities of cross-border operations and leverage regional synergies.
• Cultural Fit: Understanding the specific company culture and finding a candidate who could seamlessly integrate into the existing team dynamic was paramount. This fostered collaboration and ensured smooth onboarding.
• Business Growth Expertise: We sought candidates with a demonstrable history of driving business growth in fast-paced environments. This included experience in building high-performing teams, scaling operations, and capitalizing on emerging market opportunities.
• Language Proficiency: Fluency in English was essential for effective communication with international stakeholders and headquarters.

By implementing this targeted approach and rigorous screening process, we were able to place a strategic Head of Sales within a swift 87-day timeframe. However, achieving this executive placement demanded a keen eye for detail and a willingness to walk away from candidates who didn’t perfectly align with the client’s needs. For instance, we declined a highly qualified candidate with impressive sales experience in the LATAM region. Upon closer examination, we discovered their success was primarily concentrated in their home country. They lacked the demonstrable experience navigating the regulatory nuances and market variations present across different LATAM markets.

Furthermore, we also provided our client with valuable insights into the regional compensation structures. We pulled data that supported the hypothesis that standard compensation for this role was about 25% higher than the client’s starting range. By offering competitive compensation aligned with market expectations, we were able to attract a pool of highly motivated and qualified candidates.

Client Impact

Our executive leader placement resulted in a significant impact for our client. By filling the Head of Sales role with a skilled and qualified decision maker, the client was able to:

• Develop a Comprehensive Regional Growth Strategy: The newly appointed Head of Sales brought their expertise in LATAM markets to the table, enabling the client to formulate a data-driven and regionally focused growth plan.
• Expand Market Reach and Partnerships: The executive’s extensive regional networks facilitated the establishment of new partnerships and the expansion of the client's footprint across key LATAM markets.
• Drive Business Growth: The leadership's experience in scaling operations and capitalizing on market opportunities led to a significant increase in the client's market share and profitability within the region’s fintech landscape.

Onboard a High-Performing Executive Leader with Kingsley Gate

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10 ways marketing will power fintech success.

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Modern marketing in fintech is set to drive revenue and change perceptions.

The dynamic landscape of modern marketing has evolved within the realm of fintech. Marketing is central to a company's mission, success, profitability and trajectory. Gone are the days when marketing played a secondary role to sales functions. Instead, we’re witnessing a shift in the role of marketing. Reports show that fintech success will depend on an alignment of factors influenced by a strong marketing team. Marketing is set to amplify product development, drive sales and build partnerships. It is set to orchestrate PR initiatives, fortify brand identity, attract top-tier talent, and nurture customer relationships. Read on to hear examples of how modern marketing will power fintech.

Marketing As A Revenue Driver

Marketing is at the “heart of driving revenue,” says Payal Raina, founder of Fintech B2B Marketing Community . She urges businesses to reject the notion of it being a “cost driver.” She stresses that marketing is “a growth driver.” She says marketing “sits at the forefront of innovation and at the heart of the organization.” The entire team should link the firm’s mission, vision and monetary goals.

Marketing As An Educator

Sonia Mazzotta-Morrison is a founder of Disrupto , a fintech digital services agency. She believes that marketing should play an educational role. She explains that fintech products must “be accessible to be adopted.” She explains that fintech has a lot of jargon that needs to be “broken down and translated.” Users of any system can navigate it better and utilize its benefits if they clearly understand its impact on them.

Marketing For Consumer Personalization

Rashee Pandey agrees, saying that increasing understanding allows for “hyper-personalization.” She is the associate director of membership and growth at Innovate Finance , the U.K.’s industry body for fintech. She says, “effective marketing plays a crucial role in continuously demystifying financial products and services for consumers.” She emphasizes the need for consumers to feel assured that their financial needs are catered to, regardless of who they are and their financial situation. Marketing has the potential to personalize and educate consumers throughout their financial journey. This includes presenting tailored products, having solutions at the forefront of consumer experience and providing clarity on how those solutions can address their financial needs.

Marketing Takes Ongoing Investment

Emmy Granstrom, global head of marketing at SteelEye , says that in a time when many firms are cutting budgets, it is time to grab market share by upping your marketing budget. “Marketing paves the way for future sales and revenue, so in recessionary periods, continued investment is critical.” There is huge potential for a company to make a mark in the wider sector by not cutting back on marketing expenditure. “This represents an opportunity for marketers to grow their brands but requires a long-term outlook.”

Matt Damon Movie Dud Falls Off Netflix Top 10 Global Chart After 1 Week

How could a ukrainian drone weighing just a few pounds blow up a 46-ton russian tank the warhead is the answer, nyt strands hints spangram and answers for wednesday may 22, marketing as the voice of purpose.

Meredith Odgers founded the sustainable fintech marketing practice at BambooWorx and is now the program director of digital learning at the Cambridge Institute for Sustainability Leadership. She says we must address marketing as a “connection function” that “drives a better future.” She points out that alongside revenue considerations, there are responsibilities elsewhere, too. She notes the “purpose of marketing should be to drive human, environmental and economic value” for all, not just for profit at all costs. She calls out that marketing has great influencing power to drive the development of inclusive financial products to reach new audiences and improve financial literacy. This is seen in the inclusivity of products and how they are marketed to various audiences. When marketing “buys into purpose,” that purpose can be “seen through the whole business and right through to the customer offering.”

Marketing To Drive Partnerships

Sumeet Vermani, founder and chief marketing office of SKV Consulting , is an advocate for the partnership ecosystem. He believes the success of fintech is grounded in regulatory, technological and customer alignment. He says these partnerships boost “collaboration, go-to-market and world class customer experiences.” Marketing can be the great enabler through events, communities and thought leadership. They rally people to “come together to navigate current global economic challenges.” Improving the sector’s messaging toward collaborative growth has great benefits. A partnership approach “creates better products, for more customers and reduces missed market opportunities—a huge revenue opportunity.”

Marketing To Maintain Trust

Natasha Gay, head of client services at Inbound Fintech and founder of Alpha Alliance Consultancy , says future success is rooted in trust. She believes that marketing has a responsibility to showcase key differences across businesses. These will be found in product, diversity, technology, ethics, sustainability, talent, inclusion and mission. Natasha says knowing how to define each of these topics will be crucial. She says providing case studies and use cases will “be the key driving force to help individual firms” stand out in the future. Marketing will be able to build trust by providing evidence on how the company affects partners and customers positively.

Marketing To Excel Innovation

Mia Mohamed, head of marketing at Toqio , talks about “orchestrating more financial solutions.” She says, “fintechs that are not innovating to orchestrate more solutions probably won't succeed.” She says it is crucial that the industry keeps disrupting by seeing problems as “solutions in the working.” This will include innovation across personalization, experience and deployment. Having a better marketing strategy will drive this further and at a pace.

Marketing To Influence Perception

Vanessa Lovatt, a strategy leader for the Financial Times wanted to add to innovation. She describes fintech marketing as a constant “disruptive contributor.” Marketing can bring freshness and challenge into the community. She says it has an incredible power to influence inclusion though its messaging in the workplace and society. She says “marketers have a great opportunity to make an impact every day.” They are responsible for "sending out messages that can influence people’s perceptions.” These perceptions will go beyond simply whether people will buy or use a product. They will influence who decides to partner, who believes they can establish their career here, and who wants to join the industry.

Marketing To Remain Agile

Liesl Smith, senior vice president of global marketing at FreedomPay , believes the “consumer is constantly changing.” She highlights that marketing must understand that the customer, partner, or client has evolving needs. Marketing, therefore, should be agile, data-driven, trustworthy, authentic, and prepared to pivot. She emphasizes that businesses must understand their target audience and cater to their needs with “products that speak to them.” When there is a need, the desire and urgency to progress fintech as a whole will increase.

Marketing can influence so many facets of fintech, each of which will be pivotal to future growth and success. As economists predict a brighter economic future, it will be exciting to see the crucial role of marketing in powering growth.

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A US Trustee wants troubled fintech Synapse to be liquidated via Chapter 7 bankruptcy, cites ‘gross mismanagement’

The prospects for troubled banking-as-a-service startup Synapse have gone from bad to worse this week after a United States Trustee filed an emergency motion on Wednesday. 

The trustee is asking to convert the company’s debt reorganization Chapter 11 bankruptcy into a liquidation Chapter 7, according to court documents.

The trustee wrote that the need for Chapter 7 resulted from Synapse “grossly” mismanaging its estate so that losses were continuing with little “reasonable likelihood of reorganization” that would allow the company to emerge on the other side and carry on.

This new development is significant because Synapse founder Sankaet Pathak earlier this month alleged that its former partners owe it millions, by its own accounting, and were not paying up. Those partners have been insisting that Synapse’s allegations have “no merit.”

San Francisco-based Synapse, which operated a platform enabling banks and fintech companies to develop financial services, was founded in 2014 by Bryan Keltner and Pathak. It was providing those types of services as an intermediary between banking partner Evolve Bank & Trust and business banking startup Mercury, among others.

Synapse filed for Chapter 11 bankruptcy on April 22 and, at the same time, announced its assets would be acquired by TabaPay .

But on May 9, TechCrunch reported that TabaPay’s $9.7 million planned purchase of Synapse’s assets fell apart . At the time, Synapse said the problem was banking partner Evolve Bank & Trust. Evolve alleged that it was not involved in the sale, and was not to blame. Mercury also claimed Synapse’s allegations of being owed money had “no merit.” 

But the infighting between the companies continued. On May 13, Evolve Bank & Trust filed a motion for an order restoring access to Synapse’s dashboard system after alleging that it had been denied access to the startup’s computer systems and had been forced to freeze end user accounts.

The U.S. Trustee alleged, according to court documents, that Synapse “inexplicably cut off access to its computer systems on a weekend.”

“While disputes exist among the parties there appears to be no reasonable explanation for the Debtor [Synapse] cutting off access to its computer systems and indeed the Debtor has since represented that full access has been restored. There appears to be no dispute that these actions have played a material role in end users losing access to their funds. At a minimum, an independent fiduciary is needed to see if a resolution can be reached that minimizes further harm to depositors. For all these reasons, the Debtor has grossly mismanaged the estate and ample cause exists to convert this case to chapter 7.”

Synapse admitted that it had “no more cash or approval to use any cash after Friday, May 17.”

A hearing is scheduled for the U.S. Trustee’s emergency motion for May 17.

Hope remains that the proceedings could continue with no further shenanigans. In a creditor committee meeting that took place on May 15, shared on  LinkedIn by Fintech Business Weekly’s Jason Mikula, “it was suggested that fintech clients of Synapse might provide some kind of funding to the company to enable it to keep operating in Chapter 11, presumably in an attempt to resolve the disruption to end users.”

TechCrunch has reached out to Synapse for comment.

An Evolve spokesperson confirmed to TechCrunch that on May 11, “Evolve Bank & Trust faced an unexpected challenge when Synapse abruptly and without prior notice disabled our access to an account and transaction information dashboard controlled by Synapse and needed by Evolve. This sudden disruption significantly impacted our ability to maintain the visibility and transparency that Evolve needs to have into accounts and transactions. In response to this situation, Evolve took swift and decisive action to safeguard the security of end user funds and ensure compliance with applicable laws. As a precautionary measure, we made the difficult decision to freeze payment and card activity until we could successfully re-establish access to the dashboard as well as receive necessary account and transaction data and reports. While we understand the inconvenience this may have caused, this step was taken with the utmost consideration for the security and integrity of end user accounts. Evolve continues to work diligently to obtain necessary information from Synapse.”

The spokesperson added that Evolve has not unfrozen this activity because “Synapse has failed to provide daily transaction and account information that is necessary to process transactions…The account freeze was a precautionary measure to minimize the risks to end users and to Evolve.  At this time, Evolve is not aware of any end user funds being lost as a result of Synapse denying Evolve dashboard access.”

The previous $9.7 million purchase price that TabaPay was going to pay for Synapse’s assets are significantly lower than the over $50 million in venture capital that Synapse had raised from investors such as Andreessen Horowitz, Trinity Ventures and Core Innovation Capital over time.

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How One Company Added Carbon Estimates to Its Customer Invoices

• Robert S. Kaplan
• Timmy Melotte

A four-step playbook to help businesses increase transparency and reduce emissions.

Soprema is an international building materials supplier, producing millions of square meters of waterproofing, insulating, and roofing products each year. In 2022, Pierre-Etienne Bindschedler, the company’s president and third-generation owner, committed to reporting the carbon footprint of each product on every customer invoice, and to help customers reduce the embedded GHG emissions in the products they purchased. Paper co-author Melotte, an experienced operations director, was selected to lead a pilot project to measure and subsequently lower the carbon embedded in its products. Melotte decided to follow the E-Liability Pilot Playbook, which divides a pilot project into four stages: Project Design, Data Collection; Data Analysis, and Action. This article describes how the pilot, which focused on the company’s bitumen waterproofing systems, unfolded at Soprema. The company estimates a potential carbon footprint reduction of 34% from the project.

In 2022, Pierre-Etienne Bindschedler, the president and third-generation owner of Soprema, set a goal to develop sustainable solutions for customers. Soprema is a multi-product, family-owned business in the middle of the building materials value chain and produces millions of square meters of waterproofing, insulating, and roofing products each year.  Bindschedler wanted to report the carbon footprint of each product on every customer invoice, and to help customers reduce the embedded GHG emissions in the products they purchased.

• Robert S. Kaplan is a senior fellow and the Marvin Bower Professor of Leadership Development emeritus at Harvard Business School. He coauthored the McKinsey Award–winning HBR article “ Accounting for Climate Change ” (November–December 2021).
• TM Timmy Melotte is an Operational Excellence Director for Soprema International, a building materials supplier based in Limburg, Belgium

Partner Center

Duke settlement could mean less drastic price hikes in rate case, affordability study

Duke Energy and six other parties filed a settlement agreement Friday regarding Duke’s controversial residential electric rate increase case.

The settlement could lessen the proposed monthly rate hike for customers beginning in August and establish a Low-Income Affordability Working Group to create more programs to assist customers.

Last night, Duke and the Public Service Commission (PSC), which regulates utilities in the state, heard from customers for the final time before the PSC decides Duke’s case.

In January, Duke requested a two-part cost hike for residential electric rates that would increase costs by nearly 20%. They faced criticism from customers in the Upstate , who voiced concerns about how the cost would impact them.

Duke initially requested $323 million in increased revenue. In the settlement, they lessened the request to $240 million, a decrease of about 26%.

If the PSC adopts the settlement, a customer using 1,000 kilowatt hours each month would see an increase of about $12.53 each month beginning in August 2024 and $6.42 each month starting in August 2026.

The initial application would have cost the same customer about $5 more in 2024 and $4 more in 2026.

The South Carolina Office of Regulatory Staff, the South Carolina Energy Users Committee, the Southern Alliance for Clean Energy, the Coastal Conservation League, Vote Solar and the South Carolina Small Business Chamber of Commerce joined Duke Energy Carolinas in the settlement agreement.

Walmart and CEC Recycling did not sign the settlement agreement but noted that neither company opposed it. However, the South Carolina Department of Consumer Affairs did not support the settlement.

On Monday morning, representatives from the company and other settling parties met for a merits hearing.Because the new settlement, which is 51 pages long, was filed on Friday, the PSC and involved parties are still “trying to parse through everything,” said PSC Chair Florence P. Belser.

Consequently, Belser recessed Monday’s hearing, which will resume on Thursday, May 23, at 9 a.m. to give everyone involved more time to review the settlement.

“I'm not trying to drag this out,” Belser said. “I just want all parties and the commission to have the opportunity to be as familiar as possible with the settlement agreement and with other testimony that's before the commission.”

During Monday’s hearing, Duke’s Deputy General Counsel Camal O. Robinson said the company agreed to reduce overall revenue costs.

“The settlement specifically provides for a 26% lower revenue impact than that requested by the company, and also provides that the company will make a $2 million shareholder contribution to fund a Low-Income Affordability Study in South Carolina and low-income weatherization programs,” Robinson said.

The $2 million will come from shareholders, Robinson said, rather than customers.

According to the settlement, $1 million will go to weatherization programs , or programs that help reduce energy consumption. An example of weatherization is upgrading insulation or adding moisture control to a home.

The other $1 million will go to a study modeled after a similar Duke program in North Carolina to evaluate energy consumption for lower-income customers. The study will be completed by the end of 2025. The company claimed it would evaluate current programs and search for additional protection for customers struggling to afford their electric bills.

Duke also promised to improve their Residential Neighborhood Energy Savings program (NES).

While several parties agreed, the S.C. Department of Consumer Affairs said they could not find common ground with the company, Advocacy Director and Deputy Consumer Advocate Roger Hall said.

“The Department of Consumer Affairs did engage in good faith negotiations with all the parties in this matter. Our aim and any negotiations or any hearing is to get the best deal possible for residential customers while recognizing the needs of the other customer classes and any other interest groups,” Hall said. “Unfortunately, we were just not able to get there in this matter.”

The PSC held its final hearing for customers last night. Duke, the PSC, and the other parties involved in the settlement will meet at the next hearing on Thursday. After the hearings, the PSC will decide whether to adopt the settlement.

Sarah Swetlik covers climate change and environmental issues in South Carolina's Upstate for The Greenville News.   Reach her at [email protected] or on X at @sarahgswetlik .

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