research articles on fintech

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Published: 16 January 2024

Fintech research: systematic mapping, classification, and future directions

Qianhua Liu 1 ,
Ka-Ching Chan ORCID: orcid.org/0000-0002-8756-2991 1 &
Ranga Chimhundu 1

Financial Innovation volume 10 , Article number: 24 ( 2024 ) Cite this article

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This systematic mapping study provides a comprehensive review of current Fintech publications, analyzing the current state, maturity level, and future directions of Fintech research. Reviewing 518 Fintech articles across four academic databases from 2008 to 2021, we find a significant increase in Fintech studies, especially in Quartile 1 and Quartile 2 journals. Fintech and banking, Fintech development, and Fintech adoption are the most popular research areas, and articles in these areas are increasing. We propose a classification scheme for Fintech studies across five dimensions. Our study provides a unique perspective on the subject, enabling researchers and practitioners to re-evaluate the direction and scope of future Fintech research.

Introduction

Fintech, which is an abbreviated form of financial technology, is a term that refers to the modern relationships between Internet-related technologies and business activities in the financial services industry (Suryono et al. 2020 ). Fintech has a wide range of meanings. In business, Fintech is broad enough to describe a complete supply chain. Fintech is defined as the provision of technology to financial service providers (Dorfleitner et al. 2017 ), as well as the provision of financial products or innovative financial services (Ratecka 2020 ) characterized by sophisticated technology (Knewtson and Rosenbaum 2020 ). Fintech can also refer to companies that provide innovative digital solutions for financial services (Laidroo et al. 2021 ). Moreover, Fintech is used to describe a series of new business models that have significant impacts on the financial market and supply of financial services (Li and Xu 2021 ). Fintech can even refer to an industry that applies technology to improve financial activities (Schueffel 2016 ). In the academic context, Fintech is a cross-disciplinary subject that combines finance, technology, and innovation management (Leong and Sung 2018 ). It is possible to define Fintech as initiatives (Nicoletti et al. 2017 ) that introduce new products and technologies (Goldstein et al. 2019 ) and reduce information asymmetry in the financial industry (Li and Xu 2021 ). Fintech can also be used as an inclusion mechanism that empowers financially underprivileged individuals to gain access to the traditional financial industry. As a business and an academic term, Fintech has been applied in various contexts (Schueffel 2016 ). However, due to its nature, Fintech is Internet-based and financial-related in all contexts.

The diversity of Fintech development has resulted in its investigation across various disciplines. Thakor ( 2020 ) identified the following four areas of focus in Fintech and banking: (1) credit, deposits, and capital-raising services; (2) payments, clearing, and settlement services; (3) investment management services; and (4) insurance. They viewed Fintech as a disruptive innovation for traditional banks, especially for banks in the payment sector. Sangwan et al. ( 2019 ) undertook a thematic review of Fintech articles based on three themes—(1) industrial, (2) entrepreneurial, and (3) legal. They found that Fintech has had the most significant impact on the financial market in terms of capital and information asymmetry. Furthermore, Sangwan et al. ( 2019 ) stated that Fintech promises immense potential for further study by various stakeholders. In recent years, a few mapping studies have been performed in the Fintech field. Khan et al. ( 2022 ) analyzed 91 Fintech articles across five databases. They explored the barriers to and development of Fintech in the Gulf Cooperation Council regions and found that Fintech is a promising area for research due to its potential to provide various financial services worldwide. Ahmi et al. ( 2020 ) conducted a bibliometric analysis of Fintech research based on the Scopus database and identified basic research trends in Fintech. They suggested that although Fintech is a relatively new term, it highlights the significance of technology in the financial services industry. However, these mapping studies provided limited information on general Fintech research. Therefore, a comprehensive Fintech mapping study is required to systematically analyze the current research state and serve as a basis for future studies.

A lack of consensus among scholars and practitioners on the definition and theoretical foundations of Fintech has led to its multidimensional development across a range of meanings (Milian et al. 2019 ). Currently, the most common classification of Fintech research is in the business dimension. Suryono et al. ( 2020 ) classified Fintech research based on business models. They divided Fintech research into Fintech in general; payment, clearing, and settlement; risk management and investment; market aggregators; crowdfunding; peer-to-peer (P2P) lending; cryptocurrency; and blockchain. Takeda and Ito ( 2021 ) classified Fintech into the following four types according to company development and values derived from innovation: existing financial institutions, new entrants, new value-added, and improved efficiency. Additionally, they noted that among the articles reviewed, those addressing the new value-added by new entrants were the most numerous, whereas those examining improved efficiency by existing financial institutions were the least. Gomber et al. ( 2017 ) introduced the concept of the digital finance cube from the perspective of business administration and function. They divided Fintech into the dimensions of business functions (i.e., financing, investments, and payments), technology and technological concepts (i.e., blockchain, social networks, and near-field communication), and institutions (i.e., Fintech companies and traditional service providers). However, they viewed Fintech as an element of digital finance and did not identify frequency of studies in each dimension to present the current research state. Previous studies have demonstrated a lack of systematic dimensional differentiation in Fintech research.

Fintech, which primarily comprises startups that develop innovative services targeting specific finance-related functions, is still in its early stages of development. However, its growing prominence in the financial industry and the ongoing debates in the field have made it necessary to review and analyze Fintech research to consolidate existing knowledge and identify strategic areas for future innovation and development. Analyzing past and existing work is crucial for understanding anticipated trends in Fintech, as argued by Goldstein et al. ( 2019 ). Therefore, this study aims to bridge the gap by summarizing and analyzing current Fintech research to encompass the diverse research strands of Fintech and synthesize a comprehensive view of present and future Fintech studies. Using a comprehensive Fintech classification scheme, this study presents a systematic mapping review of Fintech studies to analyze the existing literature in both its current state and development trend and propose future research directions by answering the following research questions (RQs):

RQ1. What is the current state of Fintech research?

Rq2. what is the current maturity level of fintech research, rq3. what types of fintech does fintech research involve, rq4. what are the potential future directions of fintech studies.

The four RQs stem from the research motivation stated above. RQ1 and RQ2 aim to establish a fundamental understanding in the development of broad Fintech research. RQ3 aims to provide a systematic review of the existing types of Fintech and propose a classification scheme for Fintech studies. Finally, RQ4 aims to discuss the potential future directions of Fintech research based on the results of RQ1–RQ3.

Compared with previous studies, this systematic mapping presents a comprehensive view of Fintech research with detailed numerical data. Unlike similar mapping studies in the field, this study not only provides a simple research trend but also analyzes the situation in depth to assess the maturity level and future directions. It contributes to the literature by (a) describing the current state of Fintech studies by presenting statistical data on general trends, productive authors, and active countries in global Fintech studies; (b) identifying the maturity level of current Fintech studies by investigating the general index of research focus; (c) synthesizing the different types of Fintech into five dimensions to clarify the Fintech framework and enhance the understanding of this emerging research area; and (d) undertaking an in-depth analysis to explore future directions of Fintech studies. The study also ensures the quality of the results by considering the impact of the selected articles.

Methodology

Systematic mapping review.

A systematic mapping review is a study that collects existing literature on a specific topic (Bates et al. 2007 ) and identifies the linkages between literatures (Cooper 2016 ) for further reviews (Grant and Booth 2009 ) and categorizes them according to predefined keywords to create a coded database of literature (Bates et al. 2007 ). Unlike systematic literature reviews, systematic maps are primarily concerned with structuring a research area (Petersen et al. 2015 ) and focus on the characteristics of articles (Cooper 2016 ).

The results of the systematic mapping serve a range of functions (Bates et al. 2007 ). In addition to providing an overview of a particular topic (Kitchenham et al. 2011 ), they provide the basis for an informed decision about whether to undertake an in-depth review and synthesis of all or a subset of the studies (Grant and Booth 2009 ). A systematic mapping review can also establish whether these studies will help answer the RQs and address pragmatic considerations about the resources available to complete the review (Grant and Booth 2009 ). This mapping study applies the process described in the Social Care Institute for Excellence (SCIE) Systematic mapping guidance (Clapton et al. 2009 ; Petersen et al. 2008 ).

Mapping process

Appendix 1 presents the visual workflow of the mapping process in this study. The research process consists of four stages—exploration and preliminary work, search strategy design, research execution, and coding and analysis. The research aims were first defined. Then, the existing scope of Fintech literature was identified, followed by capturing the broad and diverse research strands using a broad definition of Fintech. As the scope of this study aims to provide a thorough exploration of Fintech research, the RQs were developed from multiple dimensions. Therefore, general and broad search strings were chosen to gather sufficient articles across various disciplines. The search strings were refined and modified through iterative test searches until a satisfactory result was obtained.

A list of articles was collected from four databases based on the inclusion criteria outlined in Table 1 . To eliminate duplicates, Endnote was initially used, followed by manual content checks. Next, a set of exclusion criteria was applied to filter out additional articles. The screening process and results of each phase are presented in Fig. 1 . Finally, the selected articles were classified, aggregated, visualized, and mapped in a way that addresses the RQs (O’donovan et al. 2015 ). The process of constructing the scheme and extracting data underwent multiple iterations to achieve optimal results. To distinguish the authors of the selected articles from the current authors (Riccio et al. 2020 ), the authors of this study are referred to as “assessors”.

Screening process

Research questions

This study aims to determine the existing scope of Fintech literature and establish a foundation for future research in the field. To achieve this, the RQs were formulated to capture the diverse articles related to Fintech.

This RQ aims to provide an up-to-date snapshot of Fintech research to determine the current state of research in the field through a cross-sectional study of four key aspects—authorship, country, article type, and impact. By examining these factors, this question seeks a static view of Fintech research and identify trends and patterns that can inform future research in this rapidly evolving field. The impact of articles will be considered alongside other aspects in this analysis.

The investigation of maturity level positions Fintech research in a dynamic state. Studying the maturity of Fintech research provides researchers with stronger intuitive insights into the development of the field. This question explores the current research focuses to identify concentrated research content and business activities in the industry.

The definitions of Fintech are often inconsistent and ambiguous (Schueffel 2016 ), which hinders a comprehensive understanding of innovative practices and developments in the industry. To address this issue, this RQ aims to broaden the scope of Fintech beyond its typical categorization by business models (Dorfleitner et al. 2017 ). By exploring diverse types of Fintech in the broadest sense, this question aims to provide a more comprehensive and nuanced understanding of the Fintech landscape.

To provide practical guidance for future research, this RQ aims to identify emerging areas in primary studies and the focus of scholars to obtain the potential research opportunities in Fintech.

Database selection

In this article, four well-known digital databases were employed for a comprehensive and quality coverage of the research area. The databases are the Association for Computing Machinery (ACM) Digital Library, Institute of Electrical and Electronics Engineers (IEEE) Xplore, Scopus, and Web of Science (WoS).

Both the ACM Digital Library and IEEE Xplore are science-related databases that mainly cover technical articles related to Fintech. The ACM Digital Library is employed for its extensive full-text articles and bibliographic literature that covers computing and information technology. IEEE Xplore provides a large number of indexed conference proceedings that allow the identification of emerging trends in research at an earlier stage (Chigarev 2021 ).

As a large database of abstracts and citations, Scopus offers a rich advanced search feature. It contains articles published in peer-reviewed journals by multiple publishers (Riccio et al. 2020 ). In addition, its multidisciplinary aspect allows researchers to easily search multiple disciplines (Burnham 2006 ). Although Norris and Oppenheim ( 2007 ) argued that Scopus is weak in the coverage of foreign journals and does not currently include social science articles published before 1996, this study is limited to articles written in English and published since 2000. As the largest data source in this study, Scopus was chosen to ensure that a wide variety of research domains are included (de Sousa Borges et al. 2014 ). WoS is a widely recognized proprietary database for peer-reviewed journal content (Mikki 2009 ). Therefore, WoS was used as a trustworthy source of quality studies, providing a depth of coverage.

Search string strategy

A systematic mapping study is generally considered less stringent (Kitchenham et al. 2011 ) as it usually focuses on the big picture and covers a large number of relevant articles in the field of study. This study employed a search string strategy of the research titles and keywords using the following keywords: “Fintech”, “Financial Technology”, “Fin Tech”, and “Fin-tech”. This strategy mainly returned articles with a higher-level and business-oriented focus rather than those with a technical or engineering focus. Additionally, articles that solely focus on blockchain and cryptocurrencies were excluded from this study. The search strings were created by combining the keywords and inclusion criteria, as presented in Table 1 .

As each database’s search facility is different, the primary search strings had to be transformed into the native syntax of each database (O’donovan et al. 2015 ). An example of a search query for the Scopus database is presented in Table 2 .

Screening of research

The screening process for this mapping study is illustrated in Fig. 1 , and the search was performed on December 14, 2021. A total of 976 Fintech-related articles were initially identified from the four selected databases, with 207 duplicates were removed using Endnote, primarily from Scopus and WoS. An additional 106 duplicates were removed manually, including pre-published papers, based on the exclusion criteria. This was done to ensure the clarity and practicality of the results.

The 663 nonduplicated articles were processed using the exclusion criteria presented in Table 3 . Only articles that directly focus on Fintech or are associated with Fintech practices or concepts are included, and studies that do not meet this criterion (28 articles) were excluded. To ensure a reliable understanding of the selected articles, this mapping study considers only those that are available in full text or have abstracts that provide sufficient information. The impact of each article has been considered, and for journal articles to be included, the journal must have a quartile rank (based on information from the SCImago database) or be listed in the WoS Master Journal List. Journals that are not assigned a quartile rank but are included in the Scopus database (usually new journals) are also included in this study. Regarding conference papers, they must be published in the Computing Research and Education Association of Australasia (CORE) conference list (“CORE Rankings Portal” 2016 ) or in either an ACM or IEEE conference proceeding. The impact criterion excluded 94 articles from this mapping study.

During the second round of screening, it was found that three articles had excessive recycled content under different titles by the same authors, and one article was a book that was misclassified by the databases. Therefore, the final number of articles included in this mapping study is 518.

Data abstraction and synthesis

To answer the RQs, the extracted data were synthesized through a data synthesis process (Li et al. 2015 ). In the data extraction step, the assessors thoroughly read, analyzed the relevant studies, and extracted all necessary information into a spreadsheet (Riccio et al. 2020 ). Afterward, the data were then grouped and synthesized for further frequency, network, and cooccurrence analyses.

The structures for answering each RQ were designed during the initial screening. For RQ1, the current state of Fintech studies is answered by classifying the statistical data of primary Fintech studies into four aspects—authors, countries, type of articles, and publication impact. Appendix 2 presents the detailed structure of data extraction. To answer RQ2, the maturity level of Fintech research was examined through an analysis of research focus and levels of activity.

In terms of RQ3, this study explored diverse types of Fintech beyond business models. Although the commonly used Fintech classification is based on business models and service types, this article refined the generalized “Fintech” by categorizing it into (1) Fintech industry; (2) Fintech business; (3) Fintech platforms, systems, and apps; (4) Fintech services and Fintech as a tool; and (5) Fintech technology. The classification was developed based on observations made from the selected articles. Furthermore, a frequency analysis of each type of Fintech was conducted to provide a comprehensive understanding of the level of activity in each category.

To address RQ4, we conducted a comprehensive evaluation of the selected articles and examined the limitations and future directions identified by the authors. Through this process, we identified gaps in the current literature and provided insights for future studies. In addition, we offered our own perspectives on the research priorities in the field.

The datasets used and analyzed during the current study are available in the Mendeley repository ( https://doi.org/10.17632/gd4hc7ym7r.3 ). Following the above systematic process, the results of this mapping study are presented below.

Results and analysis

This section presents a synthesis of the data extracted from the primary studies. A total of 518 primary studies conducted from 2008 to 2021 were analyzed to answer the four RQs. The data analysis involved a qualitative content analysis, where the assessors identified and analyzed key themes, categories, and dimensions based on the data. The assessors used their own judgment and interpretation to group and categorize the data, considering the frequency and coverage of the selected articles both geographically and thematically (Meçe et al. 2020 ). By synthesizing and organizing the findings, a comprehensive and extensive understanding of Fintech was obtained, providing valuable insights and perspectives for future research.

RQ1 What is the current state of Fintech research?

The earliest article on Fintech identified in this study was in 2008, but there was a gap until 2016. From 2016 to 2017, there was a 73% increase in the number of articles (from 11 to 19). Since 2018, there has been a significant increase of 195%, with a total of 56 articles. In 2019, there was a stable rise of 5% (from 56 to 59 articles). The number of Fintech articles continued to surge, reaching a peak in 2021 with a total of 202 articles.

To ensure the quality of the articles included in the study, their impact was considered. During the initial screening, 94 articles from journals and conferences papers were excluded as they did not meet the impact criterion (EC3). The distribution of the included articles by year and impact criteria is presented in Table 4 . Among the journal articles, 151 were published in Q1 journals, 122 in Q2, 85 in Q3, and 59 in Q4. Additionally, although 33 journal articles were not assigned a quartile ranking by SCImago, they were included in the study because they were indexed by WoS or Scopus.

The selected conference proceeding papers totaled 68, with 23 appearing in the CORE conference list, 13 in IEEE or ACM conferences, and 32 in the WoS list or Scopus list or assigned a quartile ranking in the SCImago database. While the largest increase in the number of articles occurred in 2021, most of the increase was observed in Q1 and Q2 articles.

Regarding authors

Out of the 518 selected articles, 1381 unique authors contributed to them. The top productivity level of authors was four Fintech articles each. Among these prolific authors, three of them published all their Fintech articles in Q1, WoS journals, or in more prestigious conferences, such as CORE, IEEE, and ACM. These authors can be considered the most productive in terms of publishing high impact Fintech research. In particular, the first author in Appendix 3 has published four high impact articles, which also achieved very high citation rates per year. The top productive authors with three or more articles are presented in Appendix 3 .

Countries of publications

A total of 82 countries were involved in Fintech publications, with international collaborations accounting for 25.67% (135 out of 518). Table 5 presents the top ten countries ranked by the number of Fintech articles and the number of articles in high impact journals (Q1 and WoS). China leads with 102 articles, followed by the US with 60 articles and Indonesia with 46 articles.

Type of articles

The primary studies selected for this review were limited to published journal articles and conference papers. Of the 518 studies, 450 (86.87%) were journal articles and 68 (13.13%) were conference papers, as depicted in Fig. 2 . Research articles were the most common type of journal article, comprising 68.22% (307 articles). Perspective, opinion, and commentary articles accounted for 16.67% (75 articles), while review articles accounted for 7.56% (34 articles).

Distribution of article types

Tables 6 and 7 present the most prominent journals and conferences for publishing Fintech research, respectively. Journals that have published more than five articles and conferences that have published more than three papers are included.

Table 8 presents a comparison of popular research areas in journal articles and conference papers. The analysis indicates that journal articles tend to focus on macro-level discussions of Fintech development, while conference papers are more oriented toward technology aspects.

Publication impact

Among the journal articles, 142 were published in Q1-ranked journals and listed in the WoS Master Journal List, which accounted for 31% of the total primary studies. Articles with more than 50 citations per year are summarized in Appendix 4 . The number of citations per year was calculated based on citation data from Google Scholar, with all citation windows calculated from the first available year to 2022 rather than the official publication year.

RQ2 What is the current maturity level of Fintech research?

The maturity level of Fintech research was evaluated based on the research focus and levels of activity. The research focus was analyzed in the following two ways: (1) by a matrix of research lenses and areas and (2) by conducting a keyword analysis of titles and abstracts using VOSviewer. Both approaches indicate that Fintech is a low maturity research sector that falls between technology triggers and the peak of inflated expectations (Steinert and Leifer 2010 ). The business lens reveals that Fintech research primarily focuses on startups and financing, indicating that the industry is still in a nascent stage with low maturity compared with other industries.

In the first approach, four research lenses (business, socioeconomical, technological, and political regulatory) were identified. The business lens examines the management and operations of firms as well as their development on a microeconomic scale. The socioeconomical lens focuses on macro-level social and economic development on a national, regional, or global scale. The technological lens covers the technological side of Fintech, including system development, Blockchain, and artificial intelligence (AI), etc. Finally, the political regulatory lens includes studies on national policy or regulations related to Fintech. It is possible for one study to fit into multiple lenses when it addresses multiple aspects.

The research areas were identified, summarized, categorized, and synthesized through three rounds of screening and are presented in Appendix 5 . In the first screening, the assessors thoroughly read the articles and identified the detailed research focus of each study. Then, the detailed research focus was abstracted and categorized into a general research area. In the second round, the assessors read the articles again to ensure they fit into the correct research area(s). The research areas were then synthesized into broader categories, including introduction and overview of Fintech; interaction between Fintech and industries; interaction between Fintech and institutions; interaction between Fintech and small and medium-sized enterprises (SMEs); management; innovation and development of Fintech; Fintech adoptions; Fintech ecosystems; Fintech user and service analysis; risks and issues of Fintech; sustainability; social-related areas; macroeconomy; credit systems; security; Fintech system development and maintenance; technologies in Fintech; regulation; and governance.

The third round of screening involved reading all the primary studies and assigning them to each research lens, while ensuring they are placed in the correct research category. To present the patterns in the table, the highest frequency in the research lens of each research area is highlighted in Appendix 5 . In Appendix 6 , a cooccurrence network analysis is presented to better understand the interdisciplinary relationships between different research areas and how they interact with each other. Additionally, in Appendix 7 , a cooccurrence matrix on research lenses is presented to indicate research density and centrality, providing a clear picture of the prevalence and importance of different research lenses in the selected articles.

Figure 3 depicts the outcomes of the keyword analysis using VOSviewer—an online bibliometric network visualization tool. The node size denotes the frequency of appearance in the title and abstract fields of Fintech research, with larger nodes indicating higher frequency. The analysis highlights that banking, regulation, challenge, lending, use, and adoption are the most frequently occurring words in Fintech research. The proximity of two nodes indicates their relatedness, with closer nodes indicating a stronger relationship. The analysis identifies the following four clusters: the red cluster presents keywords in the business lens, the green cluster indicates keywords in the socioeconomical lens, the yellow cluster highlights keywords in the technological lens, and the blue cluster presents keywords in the political regulatory lens. Some studies fit into multiple clusters as they discuss multiple aspects.

Keywords analysis

The keyword analysis revealed three key research areas with the highest frequency—Fintech and banking (represented by “banking” in Fig. 4 ), customer adoption of Fintech (represented by “adoption” in Fig. 5 ), and Fintech development (represented by “Fintech development” in Fig. 6 ).

Linkage of banking

Linkage of adoption

Linkage of Fintech development

In addition, keyword analysis provides insights into the relationships between different keywords. For example, in Fig. 4 , the keyword “banking” is closely related to “business”, “financial markets”, “access”, and “sustainable development”. This observation can be supported by the work of Kou et al. ( 2021 ), which suggests that banks invest in Fintech to achieve a competitive advantage in the financial market. Figure 5 depicts that the keyword “adoption” is closely related to “trust”, “Fintech service”, “benefit”, “ease (of use)”, and “intention (of use)”. In Fig. 6 , the keywords “regulation”, “regulator”, “financial inclusion”, “access”, and “challenge” are closely related to “Fintech development”. This suggests that Fintech development is heavily influenced by challenges related to regulatory policies and financial inclusions.

RQ3 What types of Fintech does Fintech research involve?

The difficulty of defining the exact boundaries of Fintech is evident in the vague definitions that have been presented in the literature (Lai and Samers 2021 ). Although Fintech is often categorized based on its distinctive business models (Dorfleitner et al. 2017 ), it encompasses a wide range of financial technology-related aspects. The objective of RQ3 was to create a clear and robust classification system for all types of Fintech for understanding the latest innovations and emerging developments in this rapidly evolving field to provide a foundation for future research.

To classify the diverse types of Fintech mentioned in the selected articles, the assessors read, abstracted, and coded them. They were organized into five distinct dimensions, as presented in Appendix 8 . The classification presented in this study adopts an industry structure framework, encompassing not only the various segments within the Fintech industry but also the regulators and supervisors overseeing it. Within this framework, the dimension of “Regulation and supervisions” oversight and compliance is explored, with topics such as regulatory sandboxes, regulatory challenges, and legislative issues frequently discussed. In addition, the category of “Fintech in general” captures broader conceptual discussions surrounding the industry, including its definition and overview, as well as its associated risks and general issues. This multidimensional classification allows for a comprehensive and nuanced understanding of the Fintech landscape and its components.

The classification scheme also identified the frequency of Fintech types discussed in the primary studies. As a single study may cover multiple types of Fintech, the numbers may overlap across categories. The number of the units and sub-units are not in an inclusion relationship but only the frequency with which each unit appeared in the selected articles. The five main Fintech categories are described below.

Fintech industry

In this study, the Fintech industry is categorized as a macro dimension (113 articles) that includes various Fintech firms and encompasses the entire supply chain of Fintech services for commercial and retail customers. Although some scholars argue that Fintech is not yet recognized as an independent industry (Wójcik 2020 ) but rather a branch of the general financial industry (Pollari 2016 ), to identify the logical flow of diverse types of Fintech, in this study, it is considered an industry rather than a segment of the financial industry.

Fintech firms

A total of 58 articles were identified that discussed Fintech firms in general. The Fintech industry comprises Fintech firms that offer both business-to-business (B2B) and business-to-consumer (B2C) services, covering technology, financial services, and other aspects of Fintech. For instance, companies that provide technology to financial service providers (Dorfleitner et al. 2017 ) were classified as Fintech firms. Similarly, companies offering nonbanking financial services, such as online insurance services and mobile money services, were also considered Fintech firms. The four main topics related to Fintech firms are (1) Fintech startups, (2) investment in Fintech businesses (Fintech investments), (3) financing solutions or problems of Fintech businesses (Fintech financing), and (4) the management of Fintech firms (Fintech management).

Fintech systems, Fintech platforms, and Fintech apps

Fintech firms are responsible for the development and ownership of Fintech systems, platforms, and apps. These technological tools enable firms to offer Fintech services and tools to their clients.

This mapping study applied the definition of Fintech platforms proposed by Dhar and Stein ( 2018 ) that Fintech platforms are complete or incomplete platforms that facilitate exchange between interdependent groups, usually consumers and producers, through a combination of channel access, functionality embedded in an information technology system, and associated key business processes. Examples of Fintech platforms are Amazon and PayPal.

In contrast, Fintech systems refer to the technology systems that provide financial services to various companies, such as online accounting systems and other software-as-a-service financial solutions. Additionally, Fintech systems encompass systems that enable Fintech services. Fintech apps are mobile applications provided by Fintech firms that allow users to access their financial services.

Fintech as tools and Fintech services

“Fintech as tools” and “Fintech services” are supported by various Fintech technologies. In this study, “Fintech as tools” refers to B2B Fintech tools used by traditional financial institutions and other industry service or product providers. These institutions adopt Fintech tools to serve their customers or streamline their business operations. Some examples of Fintech tools are online banking, chatbots, and robo-advisors.

“Fintech services” are directly offered to end users and include investment services, lending, payments, and insurance. Fintech services were the most discussed in the selected research. Within the dimension of Fintech services, P2P lending and payment, transfer, and settlement were the two most frequently discussed subunits in the selected studies.

Fintech technology

Fintech technology encompasses the various technologies utilized in Fintech services, such as the Internet of things (IoT), AI, machine learning (ML), and deep learning. As the building blocks of Fintech, these technologies support other sectors in the industry. Among the technologies discussed in the sample articles, blockchain was the most frequently mentioned, followed by AI, ML, and big data. Although they are less discussed, IoT, deep learning, and cloud computing are also important technologies that should not be overlooked in Fintech research.

RQ4 What are the potential future directions of Fintech studies?

Fintech and sustainable development

The topics discussed above prompt us to reflect on the future of Fintech and its potential impact on sustainable development. The rapid advancements and innovations in Fintech can serve as a driving force for sustainable development, while the pressing need for sustainable development can provide a compelling impetus for further Fintech innovation and progress. The interplay between these two forces is complex and multifaceted and requires careful consideration by researchers, policymakers, and industry leaders.

Fintech has the potential to significantly contribute to sustainable development, and this is a promising field that warrants further investigation. Past research suggests that Fintech can promote sustainable development in many ways. First, the innovative nature of Fintech arises from the financial industry’s pursuit of sustainability with the technology being applied to financial services to reshape existing propositions (Petrushenko et al. 2018 ) and support digital financial transformation (Arner et al. 2019 ), enabling Fintech to offer a broader range of services to customers and promote financial inclusion. Second, Fintech serves as a catalyst for technology-driven sustainable development. As a technology-driven industry, Fintech integrates technology into financial services, enabling it to act as a technology enabler (Beder 1994 ) and foster sustainable development. Third, Fintech has the potential to promote sustainable development in various industries due to its role as an intermediary and final goods provider. As a platform industry (Shin and Choi 2019 ), Fintech can integrate with almost all industries, enabling sustainable development and promoting overall economic performance. Given its potential, it is crucial to continue exploring Fintech’s role in sustainable development to identify ways in which Fintech can promote sustainable development.

Exploring innovation is essential for the future of sustainable development in the Fintech industry. Sustainable development in Fintech aims to improve existing technologies for long-term development, ensuring that current needs are met without compromising the ability of future generations to meet their needs (Rogers et al. 2012 ). To achieve sustainable innovation, the application of technology in Fintech needs to be deepened and broadened. Fintech technology serves as the foundation of the industry structure and expanding its application will enrich service categories. Additionally, deepening the industry’s foresight by developing interpretative financial datasets for analyzing and predicting anomalous financial situations can aid in sustainable innovation (T. Li et al. 2021 ).

The Fintech industry relies heavily on information and communication technology to create innovative and disruptive business models in financial services (Leong and Sung 2018 ). The urgency for Fintech innovation has increased in the post-COVID-19 era, particularly in improving financial service processes. Finally, Fintech innovation will drive research into the application of Fintech in different user scenarios. While most Fintech services are currently used as a tool to complete a business loop, expanding the scope of Fintech usage across various user scenarios is essential for sustainable development. Therefore, sustainable innovation is critical to the future of the Fintech industry. By expanding the application of technology, promoting financial innovation, and researching Fintech applications in different user scenarios, the Fintech industry can achieve sustainable development.

Discussion and conclusion

This systematic mapping study provides an extensive overview of Fintech research, including its current status, maturity level, and types of Fintech. Through a systematic review of 518 Fintech articles from 2008 to 2021 across four databases, the study reveals that Fintech is an emerging research field, and the number of Fintech articles is rapidly increasing, especially in 2021. The study also found that China, the US, and the UK are leading in both the total number of articles and high impact articles. The maturity level of Fintech research is still in its early stage, and Fintech services are the most popular research area. The study proposes future research directions, such as exploring the integration of Fintech and banking systems; assessing the continued use and perceived benefits and risks of Fintech services for end users; and investigating sustainable development of consumer protection, cross-industry cooperation, and financial regulation.

Maturity level

The maturity level of Fintech studies is investigated through the research areas and lenses. The results reveal that Fintech and banking, Fintech development, and Fintech adoption are the most popular research areas, and the number of articles is increasing. Fintech is a business-related industry that combines financial and technology in both word and content. More than half of the Fintech articles fall under the purview of the business lens. However, the number of studies in the socioeconomic and political regulatory lenses is increasing, reflecting growing social and regulatory concerns, especially in financial inclusion. Regulatory sandbox in the Fintech industry is another topic that has recently attracted attention. In terms of the maturity of research, Fintech is still in its initial stage of development, positioned in the middle of technology triggers and the peak of inflated expectations (Steinert and Leifer 2010 ). Most Fintech products or business models are in their first generation from mass customisation to personalisation. Compared with other industries, the research area of Fintech in the business lens is concentrated on startups and Fintech financing, indicating that Fintech is at a low maturity level.

Types of Fintech

The classification of Fintech can be challenging due to the large volume of articles and broad coverage. The assessors proposed a vertical classification scheme based on the most commonly appearing dimensions in current studies. In the scheme, Fintech is categorized into the following five dimensions: (1) Fintech industry; (2) Fintech firms; (3) Fintech systems, platforms, and apps; (4) Fintech as tools and Fintech services; and (5) Fintech technologies. The results reveal that while Fintech research is evenly distributed across each level, Fintech services and the Fintech industry are popular research topics currently. However, Fintech services remain a top priority for future development as the value of Fintech to its users lies in improving their experience. The structure and future development of the Fintech industry will evolve depending on the future growth and innovation of Fintech services. Regardless of the level, Fintech should always aim to be a financial solution and innovation initiator that integrates financial services, enhances customer experience, adapts to regulatory change (Pollari and Raisbeck 2017 ), and fosters cooperation between different industries driven by technology.

Future research directions

Future directions for Fintech research involve exploring the integration of Fintech and banking systems, continued use, and perceived benefits and risks of Fintech services for end users, as well as sustainable development of consumer protection, cross-industry cooperation, and financial regulation. One critical area of exploration is the impact of Fintech on sustainable development and the sustainable development of the Fintech industry itself. Fintech has the potential to contribute to sustainable development through its innovative nature, technology-driven industry, and role as an intermediary and provider of final goods. Therefore, sustainable innovation is a crucial direction for the Fintech industry, requiring the expansion and deepening of Fintech technology applications, financial innovation, and the exploration of Fintech applications in various user scenarios. Specifically, the Fintech industry has the potential to play a vital role in achieving sustainable development through its innovation and technology-driven approach.

Contributions

This mapping study contributes to the Fintech literature in several ways. First, unlike most existing reviews that assess Fintech research based on a single definition, this study integrates diverse types of Fintech and provides a comprehensive analysis with numerous data and figures. Second, this study not only presents the most recent research state but also examines the maturity of Fintech research, enabling both researchers and practitioners to evaluate the direction and scope of future research. Furthermore, the study provides a comprehensive classification that considers all types of Fintech identified in selected studies and proposes a vertical classification scheme for the Fintech category. The results provide valuable research information for scholars and practitioners and support the identification of future research areas and a unique perspective on the subject.

Limitations

This study has certain limitations as it only includes highly Fintech-focused articles. Articles that are related to Fintech but do not directly focus on it, such as those that only concentrate on blockchain or cryptocurrencies, are not covered. Therefore, future studies may explore each research subject individually and in greater detail.

Availability of data and materials

The datasets used and analysed during the current study are available in the Mendeley repository. Liu, Qianhua (2022), “Fintech research: systematic mapping, classification, and future direction”. Mendeley Data, V1, https://doi.org/10.17632/gd4hc7ym7r.1

Abbreviations

Association for computing machinery

Artificial intelligence

Business-to-business

Computing research and education association of Australasia

Financial technology

Institute of electrical and electronics engineers

Internet of Things

Machine learning

Peer-to-peer

Quartile 1, Quartile 2, Quartile 3, and Quartile 4 journals

Research question

Social care institute for excellence

Small and medium-sized enterprises

Web of science

Ahmi A, Tapa A, Hamzah AH (2020) Mapping of financial technology (FinTech) research: a bibliometric analysis. Globalization 2:2008

Google Scholar

Arner DW, Buckley RP, Zetzsche DA, Veidt R (2019) Sustainability, FinTech and financial inclusion

Bates S, Clapton J, Coren E (2007) Systematic maps to support the evidence base in social care. Evid Policy J Res Debate Pract 3(4):539–551

Article Google Scholar

Beder S (1994) The role of technology in sustainable development. IEEE Technol Soc Mag 13(4):14–19

Burnham JF (2006) Scopus database: a review. Biomed Digit Libr 3(1):1. https://doi.org/10.1186/1742-5581-3-1

Chigarev B (2021) Why IEEE xplore matters for research trend analysis in the energy sector. Energy Syst Res 4(15):44–58

Clapton J, Rutter D, Sharif N (2009) SCIE systematic mapping guidance. SCIE, London

Cooper ID (2016) What is a “mapping study?” J Med Libr Assoc JMLA 104(1):76

CORE Rankings Portal (2016) Retrieved from https://www.core.edu.au/conference-portal

de Sousa Borges S, Durelli VH, Reis HM, Isotani S (2014) A systematic mapping on gamification applied to education. In: Paper presented at the Proceedings of the 29th annual ACM symposium on applied computing

Dhar V, Stein RM (2018) Complete and incomplete fintech platforms. J Invest Manag 16(2):4–16

Dorfleitner G, Hornuf L, Schmitt M, Weber M (2017) Definition of FinTech and description of the FinTech Industry. In: Dorfleitner G, Hornuf L, Schmitt M, Weber M (eds) FinTech in Germany. Springer International Publishing, Cham, pp 5–10

Chapter Google Scholar

Goldstein I, Jiang W, Karolyi GA (2019) To FinTech and Beyond. Rev Finan Stud 32(5):1647–1661. https://doi.org/10.1093/rfs/hhz025

Gomber P, Koch J-A, Siering M (2017) Digital finance and FinTech: current research and future research directions. J Bus Econ 87(5):537–580

Grant MJ, Booth A (2009) A typology of reviews: an analysis of 14 review types and associated methodologies. Health Info Libr J 26(2):91–108

Khan S, Khan HU, Nazir S (2022) Utilizing the collective wisdom of fintech in the gcc region: a systematic mapping approach. Meas Control 56:713

Kitchenham BA, Budgen D, Pearl Brereton O (2011) Using mapping studies as the basis for further research—a participant-observer case study. Inf Softw Technol 53(6):638–651. https://doi.org/10.1016/j.infsof.2010.12.011

Knewtson HS, Rosenbaum ZA (2020) Toward understanding FinTech and its industry. [FinTech and its industry]. Manag Finance 46(8):1043–1060. https://doi.org/10.1108/MF-01-2020-0024

Kou G, Olgu Akdeniz Ö, Dinçer H, Yüksel S (2021) Fintech investments in European banks: a hybrid IT2 fuzzy multidimensional decision-making approach. Financ Innov 7(1):39. https://doi.org/10.1186/s40854-021-00256-y

Lai KP, Samers M (2021) Towards an economic geography of FinTech. Prog Hum Geogr 45(4):720–739

Laidroo L, Koroleva E, Kliber A, Rupeika-Apoga R, Grigaliuniene Z (2021) Business models of FinTechs—difference in similarity? Electron Commer Res Appl 46:101034

Leong K, Sung A (2018) FinTech (Financial Technology): what is it and how to use technologies to create business value in fintech way? Int J Innov Manag Technol 9(2):74–78

Li B, Xu Z (2021) Insights into financial technology (FinTech): a bibliometric and visual study. Finan Innov 7(1):69. https://doi.org/10.1186/s40854-021-00285-7

Li Z, Avgeriou P, Liang P (2015) A systematic mapping study on technical debt and its management. J Syst Softw 101:193–220. https://doi.org/10.1016/j.jss.2014.12.027

Li T, Kou G, Peng Y, Philip SY (2021) An integrated cluster detection, optimization, and interpretation approach for financial data. IEEE Trans Cybern 52(12):13848–13861

Liu, Qianhua (2022) Fintech research: systematic mapping, classification, and future direction. Mendeley Data, V3. https://doi.org/10.17632/gd4hc7ym7r.3

Meçe EK, Sheme E, Trandafili E, Juiz C, Gómez B, Colomo-Palacios R (2020) Governing IT in HEIs: systematic mapping review. Bus Syst Res Int J Soc Adv Innov Res Econ 11(3):93–109

Mikki S (2009) Google scholar compared to web of science. A literature review. Nord J Inf Lit High Educ 1(1)

Milian EZ, de Spinola MM, de Carvalho MM (2019) Fintechs: a literature review and research agenda. Electron Commer Res Appl 34:100833

Nicoletti B, Nicoletti W, Weis A (2017) Future of FinTech. Springer

Norris M, Oppenheim C (2007) Comparing alternatives to the Web of Science for coverage of the social sciences’ literature. J Informet 1(2):161–169

O’donovan P, Leahy K, Bruton K, O’Sullivan DT (2015) Big data in manufacturing: a systematic mapping study. J Big Data 2(1):1–22

Petersen K, Vakkalanka S, Kuzniarz L (2015) Guidelines for conducting systematic mapping studies in software engineering: an update. Inf Softw Technol 64:1–18. https://doi.org/10.1016/j.infsof.2015.03.007

Petersen K, Feldt R, Mujtaba S, Mattsson M (2008) Systematic mapping studies in software engineering. In: Paper presented at the 12th International Conference on Evaluation and Assessment in Software Engineering (EASE)

Petrushenko Y, Kozarezenko L, Glinska-Newes A, Tokarenko M, But M (2018) The opportunities of engaging FinTech companies into the system of cross-border money transfers in Ukraine. Invest Manag Finan Innov 15(4):332–344

Pollari I, Raisbeck M (2017) Forging the future-how financial institutions are embracing fintech to evolve and grow. KPMG, Sydney

Pollari I (2016) The rise of Fintech opportunities and challenges. Jassa 3:15–21

Ratecka P (2020) FinTech—definition, taxonomy and historical approach. Zeszyty Naukowe Małopolskiej Wyższej Szkoły Ekonomicznej w Tarnowie 1(45):53–67

Riccio V, Gunel J, Stocco A, Humbatova N, Weiss M, Tonella P (2020) Testing machine learning based systems: a systematic mapping. Empir Softw Eng 25(6):5193–5254. https://doi.org/10.1007/s10664-020-09881-0

Rogers PP, Jalal KF, Boyd JA (2012) An introduction to sustainable development. Routledge

Sangwan V, Prakash P, Singh S (2019) Financial technology: a review of extant literature. Studies in Economics and Finance

Schueffel P (2016) Taming the beast: a scientific definition of fintech. J Innov Manag 4(4):32–54

Shin YJ, Choi Y (2019) Feasibility of the FinTech industry as an innovation platform for sustainable economic growth in Korea. Sustainability 11(19):5351

Steinert M, Leifer L (2010) Scrutinizing Gartner's hype cycle approach. In: Paper presented at the Picmet 2010 technology management for global economic growth

Suryono RR, Budi I, Purwandari B (2020) Challenges and trends of financial technology (Fintech): a systematic literature review. Information 11(12):590

Takeda A, Ito Y (2021) A review of FinTech research. Int J Technol Manag 86(1):67–88

Thakor AV (2020) Fintech and banking: what do we know? J Financ Intermed 41:100833

Wójcik D (2020) Financial and business services: a guide for the perplexed. In: Draft chapter in the Routledge Handbook of Financial Geography (2020), edited by Janelle Knox-Hayes and Dariusz Wójcik (Forthcoming)

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Acknowledgements

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The current research study was conducted as part of Liu Qianhua's PhD research project at University of Southern Queensland under the supervision of Dr. Chan Ka-Ching and Dr. Chimhundu Ranga. No other external or internal sources of funding to declare.

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Appendix 1: research process

The graph shows the research process followed by this mapping. Applied the process from the SCIE Systematic mapping guidance (Clapton et al. 2009 ; Petersen et al. 2008 )

Appendix 2: data synthesise structure of RQ1

Appendix 3: top productive authors.

The table presents a list of the most productive authors who have published three or more fintech papers among all the primary studies
1 WoS: Inclusion of Journals or Conferences in WoS Master Journal List (Y = Included; N = Not included)
2 Citations per year are calculated based on the first online-available year

Appendix 4: articles cited more than 50 times per year

1 WoS: Inclusion of Journals in WoS Master Journal List (Y = Included; N = Not included).

Appendix 5: combination of research area and research lenses

This table shows the number of papers in each research area and lens. The business lens examines Fintech on a microeconomic scale, while the socioeconomical lens focuses on macro aspects. The technological lens looks at the technology side, while the political regulatory lens examines national policies and regulations. Studies may fit into multiple lenses.

Appendix 6: co-occurrence network analysis on research areas

This network analysis depicts the cooccurrence of each research area, with node size representing the frequency of discussions. Larger nodes indicate higher frequency of discussion. The thickness of lines reflects the strength of cooccurrence relationships between research areas. The analysis highlights that Fintech and bank, innovation and development, sustainability, and social-related areas are the most frequently discussed topics in the selected articles. Fintech and bank are closely linked to innovation and development, risk and issues, and Fintech technologies, suggesting an interconnectivity between these areas.

Appendix 7: cooccurrence matrix on research lens

This matrix presents the cooccurrence of each research lens. Most studies only focus on one research lens, indicated by the highest value in the matrix. The linkage between different research lenses can also be viewed, a larger value indicates a closer relationship between the two lenses. Notably, the business lens is intricately linked with other lenses, particularly the technological lens. In contrast, the socioeconomical lens is relatively distant from the technological lens.

Appendix 8: classification scheme of Fintech

The Fintech classification scheme presented in this table was created by the authors based on all the Fintech types that appeared in the primary studies. The Fintech types are laid out in the form of an industry structure, and the numbers in the table represent the frequency of each Fintech type discussed in the primary studies.

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Liu, Q., Chan, KC. & Chimhundu, R. Fintech research: systematic mapping, classification, and future directions. Financ Innov 10 , 24 (2024). https://doi.org/10.1186/s40854-023-00524-z

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News Releases

New Research Reveals Resilient and Growing Fintech Industry, Driven by Consumer Demand

World Economic Forum, [email protected]

A new World Economic Forum report offers important data on the fintech industry and actionable insights to support further market development and evidence-based regulation.
According to the report, the global fintech industry remains strong, with customer growth rates averaging above 50% across industry verticals and regions.
Consumer demand is the main driver of growth, and fintechs are offering tailored financial services and products to traditionally underserved segments of the population.
Read the report here . For more information on the Annual Meeting 2024, visit www.weforum.org. Share on social media using the hashtag #wef24.

Davos-Klosters, Switzerland, 18 January 2024 – A new World Economic Forum report released today shows the global fintech industry is demonstrating strength and resilience and continues, despite an unclear economic outlook, to expand financial services offerings to traditionally underserved consumers and businesses.

The Future of Global Fintech: Towards Resilient and Inclusive Growth , developed in collaboration with the Cambridge Centre for Alternative Finance (CCAF) at the University of Cambridge Judge Business School, draws from a global survey of over 200 fintech companies across five retail-facing industry verticals (digital lending, digital capital raising, digital payments, digital banking and savings, and insurtech) and six regions (Asia-Pacific, Europe, Latin America and the Caribbean, Middle East and North Africa, the US and Canada, and sub-Saharan Africa) to take the pulse of the rapidly evolving fintech ecosystem.

The report finds that the majority of financial technology companies hold a positive view of their regulatory environment, with 63% rating it as adequate. Additionally, 38% of surveyed fintechs cite the regulatory environment as a major supporting factor for their operations and growth.

However, a substantial portion of fintechs find regulatory compliance challenging and the licensing and registration processes to be problematic, indicating an area where policy-makers and regulators could make improvements.

“It is highly encouraging to see fintech performance remain strong after the COVID-19 pandemic, with average global customer growth rates above 50% from 2021-2022; however, identified headwinds such as a difficult macroeconomic climate and decreased fintech funding cannot be ignored,” said Drew Propson, Head, Technology and Innovation in Financial Services, World Economic Forum. “Overcoming these challenges and realizing sustained social and economic benefits from the fintech industry will require continued data gathering to better understand pain points and committed support from public and private sector actors within financial services.”

Of the most promising findings of the report, the survey data highlights that many fintechs are actively expanding the provision of financial services and products to underserved segments of the population, and these segments also make up a sizeable proportion of their customer base and total transaction values. While most surveyed fintechs that are targeting underserved customer groups and offering tailored products are in emerging markets and developing economies (EMDEs), fintechs in both advanced economies and EMDEs are found to have a sizeable portion of their customer base from these groups.

The report also offers actionable insights to public and private sector decision-makers to facilitate further responsible growth of the fintech industry, including the importance of collectively working to streamline compliance processes, improve consumer education and increase trust in the financial system.

“As the global fintech industry continues to grow and evolve, it is imperative that the pace of regulatory and supervisory innovation match that of financial innovation. This report highlights the importance of having an appropriate and adequate regulatory environment that is conducive for the scalable and sustainable development of fintech,” said Bryan Zhang, Executive Director and Co-Founder, Cambridge Centre for Alternative Finance. “The study findings also indicate the enormous potential of digital financial services to widen access to finance for consumers and SMEs by providing more accessible, affordable and personalized financial products and services.”

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Fintechs: A new paradigm of growth

Over the past decade, technological progress and innovation have catapulted the fintech sector from the fringes to the forefront of financial services. And the growth has been fast and furious, buoyed by the robust growth of the banking sector, rapid digitization, changing customer preferences, and increasing support of investors and regulators. During this decade, fintechs have profoundly reshaped certain areas of financial services with their innovative, differentiated, and customer-centric value propositions, collaborative business models, and cross-skilled and agile teams.

As of July 2023, publicly traded fintechs represented a market capitalization of $550 billion, a two-times increase versus 2019. 1 F-Prime Fintech Index. In addition, as of the same period, there were more than 272 fintech unicorns, with a combined valuation of $936 billion, a sevenfold increase from 39 firms valued at $1 billion or more five years ago. 2 Dealroom.co; McKinsey analysis.

In 2022, a market correction triggered a slowdown in this explosive growth momentum. The impact continues to be felt today. Funding and deal activity have declined across the board, and there are fewer IPOs and SPAC (special purpose acquisition company) listings, as well as a decline in new unicorn creation. The macro environment also remains challenging and uncertain. In such a scenario, fintechs are entering a new era of value creation. The last era was all about firms being experimental—taking risks and pursuing growth at all costs. In the new era, a challenged funding environment means fintechs can no longer afford to sprint. To remain competitive, they must run at a slower and steadier pace.

About the authors

This report is a collaborative effort by Lindsay Anan, Diego Castellanos Isaza, Fernando Figueiredo, Max Flötotto , André Jerenz, Alexis Krivkovich , Marie-Claude Nadeau , Tunde Olanrewaju , Zaccaria Orlando, and Alessia Vassallo, representing views from McKinsey’s Financial Services Practice.

In this report, we examine how fintechs can continue to grow in strength and relevance for customers, the overall financial ecosystem, and the world economy, even in disruptive times. Based on research and interviews with more than 100 founders, fintech and banking executives, investors, and senior ecosystem stakeholders, we have identified key themes shaping the future of fintechs. To help fintechs capitalize on these themes, we also provide a framework for sustainable growth, based on an analysis of the strategies used by long-established public companies that have weathered previous economic cycles.

Fintech growth then and now

The fintech industry raised record capital in the second half of the last decade. Venture capital (VC) funding grew from $19.4 billion in 2015 to $33.3 billion in 2020, a 17 percent year-over-year increase (see sidebar “What are fintechs?”). Deal activity increased in tandem, with the number of deals growing 1.2 times over this period.

What are fintechs?

We define fintech players as start-ups and growth companies that rely primarily on technology to conduct fundamental functions provided by financial services, thereby affecting how users store, save, borrow, invest, move, pay, and protect money. For the analysis of this report, we included the following fintech sectors: daily banking; lending; wealth management; payments; investment banking and capital markets; small and medium-size enterprise (SME) and corporate services; operations; and infrastructure (including embedded finance, and banking as a service). The analysis excluded cryptocurrency, decentralized finance, and insurtech.

The industry fared even better in 2021, thriving on the backs of the pandemic-triggered acceleration in digitization and a financial system awash with liquidity. Funding increased by 177 percent year over year to $92.3 billion, and the number of deals grew by 19 percent.

The funding surge proved to be a one-off event. Funding levels in 2022 returned to long-term trend levels as inflated growth expectations from the 2021 extraordinary results were reanchored to business-as-usual levels, and as deteriorating macroeconomic conditions and geopolitical shocks destabilized the business environment. The correction caused fintech valuations to plummet. Many private firms faced down rounds, and publicly traded fintechs lost billions of dollars in market capitalization. VC funding was hit hard globally and across sectors, dropping to $459.6 billion in 2022 from $683.1 billion in 2021. Fintech funding faced a 40 percent year-over-year funding decline, down from $92 billion to $55 billion. Yet, when analyzed over a five-year period, fintech funding as a proportion of total VC funding remained fairly stable at 12 percent, registering only a 0.5 percentage point decline in 2022.

Looking ahead, the fintech industry continues to face a challenging future, but there are several opportunities yet to be unlocked. Investors are adapting to a new financial paradigm with higher interest rates and inflation, which has altered their assessment of risk and reward. At the same time, the once-in-a-generation technology revolution under way is generating more value creation opportunities. Our research shows that revenues in the fintech industry are expected to grow almost three times faster than those in the traditional banking sector between 2022 and 2028. Compared with the 6 percent annual revenue growth for traditional banking, fintechs could post annual revenue growth of 15 percent over the next five years.

McKinsey’s research shows that revenues in the fintech industry are expected to grow almost three times faster than those in the traditional banking sector between 2023 and 2028.

These trends are also coinciding with—and in many ways catalyzing—the maturation of the fintech industry. Based on our research and interviews, three themes will shape the next chapter of fintech growth. First, fintechs will continue to benefit from the radical transformation of the banking industry, rapid digital adoption, and e-commerce growth around the world, particularly in developing economies. Second, despite short-term pressures, fintechs still have room to achieve further growth in an expanding financial-services ecosystem. And finally, not all fintechs are being hit equally hard during the market correction: fintechs in certain verticals and at particular stages of growth are more resilient than their peers.

Radical transformation of the banking industry

Banking is facing a future marked by fundamental restructuring. As our colleagues wrote recently, banks and nonbanks are competing to fulfill distinct customer needs in five cross-industry arenas in this new era: everyday banking, investment advisory, complex financing, mass wholesale intermediation, and banking as a service (BaaS). 3 Balázs Czímer, Miklós Dietz, Valéria László, and Joydeep Sengupta, “ The future of banks: A $20 trillion breakup opportunity ,” McKinsey Quarterly , December 20, 2022.

At the same time, macro tailwinds are powering the growth of fintechs and the broader financial-services ecosystem. Digital adoption is no longer a question but a reality: around 73 percent of the world’s interactions with banks now take place through digital channels.

Moreover, retail consumers globally now have the same level of satisfaction and trust in fintechs as they have with incumbent banks. 4 McKinsey Retail Banking Consumer Survey, 2021. In fact, 41 percent of retail consumers surveyed by McKinsey in 2021 said they planned to increase their fintech product exposure. The demand—and need—for fintech products is higher across developing economies. In 2022, for example, Africa had almost 800 million mobile accounts, almost half of the whole world’s total. 5 The state of the industry report on mobile money , GSM Association, April 2023.

B2B firms’ demand for fintech solutions also is growing. In 2022, 35 percent of the small and medium-size enterprises (SMEs) in the United States considered using fintechs for lending, better pricing, and integration with their existing platforms. And in Asia, 20 percent of SMEs leveraged fintechs for payments and lending. 6 McKinsey 2022 US SMB Banking Survey, 2022 (n = 955).

To capitalize on this demand, fintechs will need to keep up with fast-evolving regulations and ensure they have adequate resources and capacity to comply. Some European Union member states, such as Ireland, are bringing buy-now-pay-later providers under the scope of financial regulation. 7 Miroslav Đurić and Verena Ritter-Döring, “Regulation of buy-now-pay-later in the EU: New regime on the horizon,” Law Business Research, February 8, 2023. Meanwhile, the US Consumer Financial Protection Bureau aims to issue a proposed rule around open banking this year that would require financial institutions to share consumer data upon consumers’ requests. 8 Farouk Ferchichi, “The US is one step closer to making open banking a reality,” Finextra, January 19, 2023. This would make it necessary for fintechs to ensure they have the available resources and capacity to respond to these requests.

A nascent industry in an expanding ecosystem

The banking industry generated more than $6.5 trillion in revenues in 2022, with year-over-year growth in volume and revenue margins. 9 “ McKinsey’s Global Banking Annual Review ,” McKinsey, December 1, 2022. Given the fintech market dynamics, this suggests there is still plenty of room for further growth in both public and private markets.

In 2022, fintechs accounted for 5 percent (or $150 billion to $205 billion) of the global banking sector’s net revenue, 10 Net revenue equals revenue after risk minus direct costs. according to our analysis. We estimate this share could increase to more than $400 billion by 2028, 11 Estimate based on historical growth at regional level and expert inputs from regional leaders in the banking industry (for example, forecast of roughly 80 percent 2021–22 revenue increase in Latin America). representing a 15 percent annual growth rate of fintech revenue between 2022 and 2028, three times the overall banking industry’s growth rate of roughly 6 percent (Exhibit 1).

Emerging markets will fuel much of this revenue growth. Fintech revenues in Africa, Asia–Pacific (excluding China), Latin America, and the Middle East represented 15 percent of fintech’s global revenues last year. We estimate that they will increase to 29 percent in aggregate by 2028. On the other hand, North America, currently accounting for 48 percent of worldwide fintech revenues, is expected to decrease its share to 41 percent by 2028.

While fintech penetration in emerging markets is already the highest in the world, its growth potential is underscored by a few trends. Many of these economies lack access to traditional banking services and have a high share of underbanked population. Fintechs have had some success in addressing these unmet needs. In Brazil, for example, 46 percent of the adult population is said to be using Nubank, a fintech bank in Latin America—double the share two years ago. 12 Oliver Smith, “Nubank turns $141m profit in Q1 as Brazilian market share nears 50%,” AltFi, May 16, 2023.

Moreover, while the market cap of private fintech companies has increased substantially over the past decade, the sector’s penetration of the public market remains small. 13 Michael Gilroy, Chase Packard, and Leslie Wang, Fintech and the pursuit of the prize: Who stands to win over the next decade? , Coatue, October 24, 2022. In the eight years leading up to October 2022, 44 modern fintechs (those that were founded in 1999 or later and went public after 2014) did an IPO, creating a combined market cap of $0.3 trillion. In contrast, during the same period, there were more than 2,500 legacy public financial-services companies (whose average year of founding was 1926) with a combined market cap of $11.1 trillion. 14 Michael Gilroy, Chase Packard, and Leslie Wang, Fintech and the pursuit of the prize: Who stands to win over the next decade? , Coatue, October 24, 2022.

Not all fintech businesses are created (or funded) equal

Last year was turbulent for fintechs, but there were differences in the fundraising performance of firms based on maturity and segments.

Maturity stage

Companies in the growth stage (series C and beyond) showed the highest sensitivity to last year’s funding downturn, with a sharp year-over-year funding decline of 50 percent. Meanwhile, fintechs in the early seed and pre-seed stages were more resilient and increased funding by 26 percent year over year (Exhibit 2). This funding outperformance of firms in the early and pre-seed stages was a consequence of the longer time to maturity, which gives start-ups more time to get through periods of economic uncertainty and recover any losses before an eventual sale.

Funding for B2B fintech segments last year was more resilient than for those in B2C, with smaller funding declines (Exhibit 3). The two B2B verticals that were least affected were (1) BaaS and embedded finance and (2) SME and corporate value-added services. These two verticals recorded year-over-year funding declines of 24 and 26 percent, respectively. In contrast, funding for payments-focused fintechs dropped 50 percent. Even then, payments and lending received the largest shares of total fintech funding.

Funding for B2B segments grew at more than 25 percent annually between 2018 and 2022, driven by an increasing number of businesses adopting off-the-shelf solutions provided by digital-native firms (including payments, open banking, and core banking technology) to address challenges arising from using legacy banking infrastructure—for example, limited flexibility, slower speed, and high costs.

Many businesses continue to rely on legacy banking infrastructure that limits flexibility and speed and can often be more costly. To address these challenges, businesses are benefiting from using off-the-shelf solutions provided by digital natives for services such as payments, open banking, and core banking technology.

For BaaS and embedded finance, demand is led by customer-facing businesses looking to control their users’ end-to-end experience. Meanwhile, SMEs have been underserved by traditional financial-services providers, despite the fact they represent about 90 percent of businesses and more than 50 percent of employment worldwide. 15 “Small and medium enterprises (SMEs) finance,” The World Bank, accessed October 10, 2023. And in developing countries, the finance gap for micro, small, and medium-size enterprises (MSME) is estimated to be approximately $5 trillion, or 1.3 times the current level of MSME lending. 16 “MSME finance gap,” IFC, accessed October 10, 2023. Fintech firms have successfully addressed some of SMEs’ needs worldwide, especially in developing countries.

The path to sustainable growth

The current churn in the markets makes it prudent for fintechs to define their next move carefully. After all, they are operating in a much different environment than in years past. In their hypergrowth stage, fintechs had access to capital that allowed them to be bold in their business strategy. They could make revenue generation their foremost objective; profits were expected to follow.

The narrative has shifted since last year. The time between funding rounds for fintechs increased by more than five months from the first to the fourth quarter of 2022. The average value of funding rounds decreased by 50 percent over the same period. 17 “SVB’s challenges will accelerate valuation down rounds, startup mortality, and layoffs,” CB Information Services, March 15, 2023. These changes are forcing fintechs to find newer ways to extend runways and adjust their operating models to make decreasing amounts of cash last longer.

The days of growth at any cost are behind the industry, for now at least. In a liquidity-constrained environment, fintechs and their investors are emphasizing profitability, not just growth in customer adoption numbers or total revenues. “In the past, the reward went to fintechs that showed growth at all costs, which led to healthy valuations,” said one Africa-based growth equity investor. “Now it is about the sustainability of the business, the addressable market, and profitability.”

In a liquidity-constrained environment, fintechs and their investors are emphasizing profitability, not just growth in customer adoption numbers or total revenues.

So how can fintechs get on a path of sustainable, profitable growth?

In 2019, McKinsey conducted an in-depth study of the growth patterns and performance of the world’s 5,000 largest public companies over the preceding 15 years. The researchers’ analysis identified ten rules for value-creating growth. 18 Chris Bradley, Rebecca Doherty, Nicholas Northcote, and Tido Röder, “ The ten rules of growth ,” McKinsey, August 12, 2022. According to the research, companies that set growth strategies addressing all available pathways to growth were 97 percent more likely to achieve above-peer profitable growth. 19 “ Choosing to grow: The leader’s blueprint ,” McKinsey, July 7, 2022.

This set of rules adopted by public companies that have lived through economic cycles and periods of uncertainty can also be useful for fintechs as they transition to a sustainable growth model. Based on our analysis of these rules and interviews with more than 40 fintech industry leaders, we expect four pathways to deliver the most impact for fintechs.

Cost discipline

When fintechs had access to abundant cash and funding was easy, they placed more emphasis on growing rapidly than on managing costs. Targeted cost savings have become a bigger priority today, as fintechs seek ways to lower expenses and achieve profitability while maintaining customer satisfaction and pursuing customer growth and acquisition. Our research has found that 50 percent of public fintechs (following their IPO) were profitable in 2022. And the key differentiator between profitable and nonprofitable fintechs was cost management, not revenue growth (Exhibit 4). While both categories recorded year-over-year revenue growth of 13 percent, profitable fintechs posted a median 3 percent decrease in costs. Nonprofitable fintechs, in contrast, saw costs rise by 27 percent, which affected their profit margins.

Successful implementation of cost management efforts is the key for fintechs in their next phase of evolution. Several leaders are already making moves: 60 percent of our survey respondents said their firms are significantly managing costs. An executive at an African mobile payments firm said they are now negotiating every cost and making sure the firm is thinking for the long run.

Consider the example of the Indian fintech company Paytm, which specializes in digital payments and financial services. The firm had had a target of achieving breakeven by September 2023 but was able to achieve this six months ahead of schedule. It did so through disciplined cost management, revenue growth across businesses, and a business model with strong operating leverage. 20 “Our discipline in cost management sustains and grows profitability,” Paytm, February 20, 2023.

While fintechs establish a clear focus on costs, they should also consider adjusting how they operate, thereby creating a more agile and flexible organization that can deal with the current environment. Around 80 percent of the interviewed fintechs report that they are currently making changes to their operating models. Of these, 66 percent cite a focus on profitability and a sustainable cost structure as being among their top three reasons. Such adjustments to the operating model are most sustainable when institutions also reinforce the control functions to protect customers and stay on top of regulatory changes.

A shift from hypergrowth to sustainable growth would also result in a greater focus on strong unit economics. To do this, fintechs ensure that the profitability view is embedded across the business. For example, assessment of the value of adding new customers would evolve from efficiency-only metrics such as the customer acquisition cost (CAC) to a more holistic approach. In this example, one way to embed profitability into acquisition investment and decision making is to compare the CAC with the projected lifetime value (LTV) of a customer, using the LTV/CAC ratio to assess the marginal return on investment for acquiring every new customer. In Latin America, for example, 68 percent of fintechs self-reported an LTV/CAC greater than five, which indicates a potential for fintechs to increase spending and further fuel growth without sacrificing profitability.

Measured growth

As leaders develop growth strategies, an important question is where growth should come from. Fintechs can grow sustainably by taking three steps: building a strong core, expanding into adjacent industries and geographies, and shrinking to grow. Identifying which steps will be most accretive to growth will depend on the unique circumstances of each fintech; some might find value in pursuing all three steps, while others could choose to focus on one. Regardless of the circumstances, this decision will have greater longer-term consequences in the current environment, compared with the earlier high-funding phase.

Focus on building a strong core as a precursor for expansion

The first step in cracking the growth code involves focusing on the local market and developing a healthy core business. According to our research, companies that focus on their core business and have a strong home market are 1.6 times more likely to generate peer-beating returns. 21 Chris Bradley, Rebecca Doherty, Tido Röder, and Jill Zucker, “ Growth rules: Which matter most? ,” McKinsey, March 6, 2023.

For fintechs, the key will be to relentlessly focus on growth in their core business. As a North American fintech executive told us: “It’s a bit of back to basics. On a core product or offering, 18 to 24 months ago, you would have built additional pieces on it to upsell and cross-sell. Now, we’re looking to double down on the core business and make sure it’s a stable, viable operation.”

To do this, fintechs must tailor their value propositions to their focus markets. Let’s take the example of B2C fintechs. Our recent research (McKinsey’s Retail Banking Consumer Survey and Global Banking Pools ) quantified the potential drivers for growth at B2C fintechs. Cross-selling will likely drive growth for fintechs in emerging economies, while those in developed countries will likely see greater growth from capturing new customers. Around 72 percent of revenue growth for companies in Brazil, for example, is expected to come from cross-selling, in contrast with 25 percent and 30 percent for the United Kingdom and the United States, respectively, with the remaining growth coming from new customers (Exhibit 5). There is arguably less potential for new-customer development in developing economies, given their high fintech penetration.

Across the competitive landscape, as markets are highly heterogenous, a dedicated strategy for each region is recommended. For example, our analysis found that in the United Kingdom and the United States, fintech revenue share is split almost equally between incumbent digital banks and pure fintech players. In contrast, digital incumbents in Germany and pure fintech players in Brazil could dominate banking’s revenue share in their respective markets.

Expand into adjacent segments and geographies

After building a strong core, fintechs can consider expanding into other segments and geographies as a second source of growth. According to our previously published research, companies that do so are 1.2 to 1.3 times more likely to generate sizable returns than peers that focus solely on their core. 22 Chris Bradley, Rebecca Doherty, Tido Röder, and Jill Zucker, “ Growth rules: Which matter most? ,” McKinsey, March 6, 2023.

Today, however, expansion is no longer a must-do strategy. It may be most advantageous for companies that have strong footholds in their core markets and can use some competitive or ownership advantage to expand elsewhere. The key is to pursue measured, value-creating growth. A case in point is OPay, which started as a mobile money platform in Nigeria and has since expanded across financial-services verticals. OPay now offers peer-to-peer payments and merchant and card services.

Shrink to grow

Fintechs are moving from hypergrowth to sustainable growth, but that growth may not necessarily be consistent across all parts of the business. If fintechs divest from underperforming parts of their portfolios and scale back from regions recording limited growth, they can reinvest that capital into high-performing segments—a strategy we call “shrinking to grow.” In our research, companies that use this approach are 1.4 times more likely to outperform their peers.

“In the past, many fintechs expanded geographically, even if it didn’t make much sense,” an executive at a Latin American fintech told us. “Now they will have to focus on their profitable segment and geography and stop expanding where they are not.”

Some fintechs have been deliberate about using a shrink-to-grow strategy, changing track if an expansion strategy did not materialize as expected or the local market had more potential for growth. German robo-adviser Scalable Capital, for example, announced plans to discontinue its Swiss operations as of 2020 to focus on other markets because the implementation of the Financial Services Act in Switzerland would have required the company to manage two regulatory frameworks simultaneously. Meanwhile, Wealthsimple, a Canadian online investment platform, exited from the United Kingdom and the United States in 2021 to concentrate on its local retail market and expand its product portfolio into new financial-services areas. Similarly, in late 2020, San Francisco–based fintech LendingClub shut down its retail peer-to-peer platform called Notes to focus on other products.

Programmatic M&A

Many companies will conclude they can achieve the steps outlined in this report—launching new features, building new capabilities, and pivoting toward new revenue streams and segments—more swiftly through thoughtful acquisitions and partnerships than by relying on pure organic development. Fintech firm Block, for example, completed its acquisition of the buy-now-pay-later platform Afterpay in January 2022 to accelerate its strategic priorities for its seller and cash app ecosystems. 23 “Block, Inc. completes acquisition of Afterpay,” Block, January 31, 2022. Nearly 60 percent of fintech executives in our survey told us they are considering an acquisition in the next 18 months.

Moreover, with IPO and SPAC (special purpose acquisition company) activity slowing considerably since last year, many fintechs that might otherwise go public are turning to private markets for funding. Take the example of the British fintech Zopa, which intended to list by 2022 but eventually decided to put IPO plans on hold in response to challenging market conditions. In the interim, the firm has been raising capital from its shareholders, including $92 million in February. 24 “Zopa raises £75 million,” Zopa Bank Limited, February 1, 2023.

M&A transactions increase significantly during periods of economic uncertainty, when they also tend to deliver higher returns. During the global financial crisis, around 45 percent of banking M&A deals showed positive excess two-year total shareholder returns (TSR) between 2007 and 2009. 25 As of the year of the deal’s announcement. In comparison, less than 30 percent of banking deals posted positive excess two-year TSR between 2010 and 2020. 26 McKinsey Fintech Quarterly Radar, Q1 2023. Across industries, companies actively making acquisitions worth 10 percent or more of their market cap in total had an average TSR of 6.4 percent between January 2007 and January 2008, compared with −3.4 percent for the less active companies. 27 Brian Salsberg, “The case for M&A in a downturn,” Harvard Business Review , May 2020.

However, not all M&As are successful. Many fail to create value due to contrasting values and cultures, mismatched product–market fit, and inflated revenue forecasts in the pursuit of customer engagement and growth at all costs.

Keeping the culture alive

What has made fintechs so disruptive over the years? The answer lies largely in their ability to innovate and differentiate. Since fintechs are not as encumbered by legacy systems and processes, they can be more agile in using emerging technologies to anticipate and solve customer needs. Typically, they also have a customer-centric and collaborative approach to deliver innovation with cross-skilled teams.

Innovations have happened across fintech verticals. Neobanks like Chime and Monzo, designed around a simple and intuitive user experience, have changed assumptions about the role of branches in traditional retail banking. In the United Kingdom, for example, the total number of bank and building society branches fell by 40 percent between 2012 and 2022. 28 Lorna Booth, Statistics on access to cash, bank branches and ATMs , House of Commons, September 1, 2023. Robo-advisers such as Wealthfront and Nutmeg disrupted the traditional wealth management industry by offering low-cost, accessible alternatives to individuals lacking access to personalized financial advice. Funding Circle introduced the peer-to-peer lending concept to the financial sector, bypassing traditional banks (which had owned this relationship) and enabling direct lending between parties.

Incumbents are fast catching up with these innovations by ramping up investments in new technologies. Around 94 percent of banks in a recent survey said they plan to invest more in modern payments technology to support end user demand for better payment capabilities over the next two to three years. Of these, 65 percent said they intend to make significant or moderate levels of investment. 29 “94% of banks eyeing investment in modern payment tech, to keep pace with fintech innovation,” Finastra press release, March 8, 2023. Many incumbents are also partnering with BaaS platforms to overhaul their digital capabilities. Examples include Fifth Third Bank’s acquisition of Rize Money in May 2023 and NatWest Group’s partnership with Vodeno Group in October 2022 to create a BaaS business in the United Kingdom.

Generative AI and the future of banking

Artificial intelligence (AI) technologies are increasingly integral to the world we live in, and investors are taking notice. Generative AI is among the advanced technologies for which investments are accelerating, thanks to its potential to transform business. According to McKinsey research published in June 2023, generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually across as many as 63 use cases.

Generative AI’s impact on the banking industry will be significant, delivering benefits beyond existing applications of AI in areas such as marketing. As our colleagues have written, this technology could generate an additional $200 billion to $340 billion annually in value, arising from around 2.8 to 4.7 percent increase in the productivity of banking’s annual revenues—if the use cases are fully implemented. 1 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. For fintech, we expect a commensurate impact, if not more, given the already high exposure to tech.

Generative AI’s impact—and resulting reinvention—will span three broad categories:

Automation. Half of today’s work activities could be automated between 2030 and 2060, according to McKinsey estimates. 2 “ The economic potential of generative AI: The next productivity frontier ,” McKinsey, June 14, 2023. Fintech firm Intuit, for example, has introduced a generative AI operating system on its platform. Its custom-trained large language financial models specialize in solving tax, accounting, cash flow, and personal finance challenges, among others. 3 “Intuit introduces generative AI operating system with custom trained financial large language models,” Intuit press release, June 6, 2023.
Augmenting and enhancing productivity to do work more effectively. Generative AI could enable labor productivity growth of 0.1 to 0.6 percent annually through 2040, depending on the rate of technology adoption and redeployment of workers’ time to other activities. Morgan Stanley is building an AI assistant using GPT-4 to help the organization’s wealth managers quickly find and synthesize answers from a massive internal knowledge base. 4 “Morgan Stanley Wealth Management announces key milestone in innovation journey with OpenAI,” Morgan Stanley press release, March 14, 2023.
Acceleration. Organizations can use generative AI to extract and index knowledge to shorten innovation cycles, thereby enabling continuous innovation.

To capture these opportunities, fintechs need an ecosystem of capabilities and partners that will allow them to move fast. First movers will accrue competitive advantage as they build their capabilities and mobilize with a focus on value, rather than rushing to deliver pilots. To do this, fintechs should consider investing more in people and change management, given generative AI’s unique potential to influence the future of work. Fintechs could think about developing a medium- to longer-term talent strategy and find ways to emphasize change management and adoption. Fintechs that delay building their capabilities risk becoming the disrupted instead of the disruptors.

To retain their competitive advantage, fintechs must continue to innovate. The next big disruptor is always around the corner. Technologies like generative AI are predicted to revolutionize the competitive landscape of finance over the next decade (see sidebar “Generative AI and the future of banking”). WeBank’s CFO Arthur Wang is one executive who appreciates the urgency. He told us, “Even though our bank has been around for almost eight years, we consider ourselves a start-up. We’re always exploring better fintech technology. WeBank’s strategy is to provide better, more inclusive financial services—to the mass population as well as small and medium-size enterprises—with leading technology. We do business 100 percent online, so we rely on technology.” 30 See “ Making financial services available to the masses through AI ,” McKinsey, August 9, 2022.

A tight labor market has also made it more challenging for fintechs to attract and hire tech talent. Our survey uncovered a shift in the perception of fintechs as riskier employers. As a Europe-based fintech executive told us: “Fintechs are less attractive now because it is clearer that it is a ‘high risk’ job compared with established institutions. On the other hand, large fintechs are laying off, which can create a new pool of talents to attract.”

In such an environment, fintechs must work toward strengthening their culture and mission and, consequently, their hiring strategy. One European payments fintech, for example, has differentiated strategies based on the profile of open roles. An executive at the firm says it has been easier to recruit people for junior roles, since these workers are more eager to join a growing organization. “It is a different story with experienced profiles—for example, management team or 35-plus years—where recruiting is more difficult and retention is crucial,” he said. To attract such people, the firm offers stock options and other incentive packages. Meanwhile, an Africa-based payments and remittances fintech casts a more global net: “We hire globally, regardless of location, gender, or race,” an executive told us. “We have no quotas and try to just find the best person for each role.”

The fintech industry is undergoing a sea change, so players will have to evolve to survive. Approaches will vary, depending on each fintech’s maturity level and its vertical and geographic focus. The framework for sustainable growth, described in this report, provides a strong foundation:

Measured growth based on a stable core. Ensure there is a strong and stable core business with a targeted and proven market fit before expanding, rather than trying to grow while strengthening the core.
Programmatic M&A. Pursue M&A strategically and establish mutually beneficial partnerships based on a programmatic strategy rooted in value sharing (with incumbents and other fintechs), as opposed to pursuing M&A only as a response to a low-valuation environment.
Cost discipline. Control costs to withstand the new funding environment while remaining flexible, nimble, and compliant.
Keep the culture alive. Maintain the agility, innovation, and culture that have been the bedrock of disruption so far.

Decisions taken today will likely set the pace for fintechs over the mid to long term. The present conditions therefore call for a careful evaluation and focused implementation.

Lindsay Anan is an alumna of McKinsey’s San Francisco office, where Alexis Krivkovich and Marie-Claude Nadeau are senior partners; Diego Castellanos Isaza is a consultant in the London office, where Fernando Figueiredo is a partner and Tunde Olanrewaju is a senior partner; Max Flötotto is a senior partner in the Munich office; André Jerenz is a partner in the Hamburg office; and Zaccaria Orlando and Alessia Vassallo are associate partners in the Milan office.

The authors wish to thank Sonia Barquin, François Dorléans, Carolyne Gathinji, Eitan Gold, Carolina Gracia, Sheinal Jayantilal, Uzayr Jeenah, Yelda Kayik, Mayowa Kuyoro, Marina Mansur, Farid Minnikhanov, Bharath Sattanathan, Rinki Singhvi, and Katharine Watson for their contributions to this report.

This report was edited by Arshiya Khullar, an editor in the Gurugram office.

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Fintech and the Future of Finance

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This report explores the implications of fintech and the digital transformation of financial services for market outcomes on one side, and regulation and supervision, on the other, and how these interact.

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Fintech, the application of digital technology to financial services, is reshaping the future of finance– a process that the COVID-19 pandemic has accelerated. The ongoing digitization of financial services and money creates opportunities to build more inclusive and efficient financial services and promote economic development. Fintech is transforming the financial sector landscape rapidly and is blurring the boundaries of both financial firms and the financial sector. This presents a paradigm shift that has various policy implications, including:

Foster beneficial innovation and competition, while managing the risks.
Broaden monitoring horizons and re-assess regulatory perimeters as embedding of financial services blurs the boundaries of the financial sector.
Be mindful of evolving policy tradeoffs as fintech adoption deepens.
Review regulatory, supervisory, and oversight frameworks to ensure they remain fit for purpose and enable the authorities to foster a safe, efficient, and inclusive financial system.
Anticipate market structure tendencies and proactively shape them to foster competition and contestability in the financial sector.
Modernize and open up financial infrastructures to enable competition and contestability.
Ensure public money remains fit for the digital world amid rapid advances in private money solutions.
Pursue strong cross-border coordination and sharing of information and best practices, given the supra-national nature of fintech.

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Fintech and the Future of Finance: Market and Policy Implications

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Jul 13, 2023 Digital financial services bridging the SME financing gap
Apr 19, 2023 Central banks and innovation
Apr 17, 2023 Innovation in payments: Opportunities and challenges for EMDEs
Mar 07, 2023 Embracing the promise of Fintech responsibly through regulation and supervision
Feb 24, 2023 Fintech and financial services: Delivering for development

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The Fintech Activity note takes stock of available fintech-related data, to document patterns of fintech activity across the world, and to help identify enabling factors.

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Global Market Survey: Digital Technology and the Future of Finance Survey

The Fintech Market Participants Survey discusses findings from the survey whose responses span 330 market participants from 109 countries.

Fintech and the Digital Transformation of Financial Services

The Market Structure note draws on the underlying economics of financial services and their industrial organization to examine the implications of digital innovation for market structure and attendant policies.

Regulation and Supervision of Fintech

The Regulation note aims to provide regulators and supervisors in emerging markets and developing economies (EMDEs) with high-level guidance on how to approach the regulating and supervising of fintech.

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Consumer Protection Implications of Fintech

The Consumer Protection note provides an overview of new manifestations of consumer risks that are significant and cross-cutting across four key fintech products: digital microcredit, P2PL, investment-based crowdfunding, ...

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Innovation in Payments

The Payments note discusses the most significant innovations in payments and their key impacts and implications on users, banks and other payment service providers, regulators, and the overall structure of the payments ...

Fintech and SME Finance: Expanding Responsible Access

The SME note discusses policy and regulatory approaches that can facilitate access to finance for small and medium enterprises (SMEs) through digital financial services.

What Does Digital Money Mean for EMDEs?

The Digital Money note categorizes new digital money proposals including crypto-assets, stablecoins, and central bank digital currencies; assesses the supply and demand factors for their adoption; and lays out particular ...

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Original research article, a bibliometric analysis of fintech trends and digital finance.

Department of Administrative Sciences, Applied College, University of Bisha, Bisha, Saudi Arabia

Digital finance has piqued the curiosity of academics, students, and institutions all around the globe for more than a decade. Innovative financial services companies are offering a wide range of new financial products and new ways of interacting with customers via digital finance (Fintech). Research on finance and information systems has thus examined these shifts as well as the implications of technological advancements on the financial industry. Through presenting a bibliometric analysis, the article summarizes how scientific research has developed on the connections between financial technology developments and digital finance during the previous years. According to the ScienceDirect database, we base this literature review on journals and articles that have been published. We conducted a content analysis of 343 articles based on the discovered clusters, finding research gaps and suggesting actionable areas for further study. The results offer a solid path for future research in this area. We discuss the significance of the aforementioned publications and articles as well as potential areas of future study. The next step is to analyze the citation linkages between the most important articles to identify how they are related to one another. For financial technology research, the study looks at the way they are organized. The research is concerned with the roles of Fintech and the limits of research in digital financing. We point out potential routes for researchers to take to expand on current knowledge while also seeking possibilities for new, interesting, and creative research that adds to the expansion of the topic of research.

Introduction

The financial industry has witnessed continuous development in providing services due to digitization ( Brandl and Hornuf, 2020 ; Kanungo and Gupta, 2021 ). This improvement is distinguished by increased communication and better information processing in the client interface and back-office processes. Recently, the emphasis on digitization has shifted from enhancing the performance of conventional tasks to mainly creating employment possibilities and new business models for financial services firms ( Gomber et al., 2017 ; Legner et al., 2017 ). Digital finance includes many new financial products, financial companies, related financial programs, and new forms of customer interaction ( Anjum et al., 2017 ; Azizi et al., 2021 ) and interaction offered by financial technology companies and innovative financial services providers, for e.g., Barras (1990) , Gomber et al. (2017) , and Ozili (2018) . In light of this, research on finance and information systems has started to examine these shifts as well as the financial sector’s influence on digital development. Financial technology appears in a short time and attracts much attention from practitioners. Why ?

The answer is the ability to switch supply chain networks in almost all business sectors. New business models and technology concepts provide the foundation for innovative financing solutions, knowledge sharing within a firm, and organizational innovation ( Abbas et al., 2019a ) and knowledge management and sustainable organizational innovation ( Abbas et al., 2020 ), including intelligent, easy-to-use, time and time financial services, and lower costs ( Teece, 2010 ; Gomber et al., 2017 ; Varga, 2017 ). Some studies identified a link between the conflicting and creative characteristics of social media and the paths for future research by providing a better understanding of how social networks on the Internet are used ( Abbas et al., 2019b ; Abbas et al., 2019c ; Lebni et al., 2020 ; Liu et al., 2021 ). Also, results indicated that corporate social responsibility presented a positive impact on firms’ sustainable performance. Also, therefore, there is a definite necessity to employ media or communication resources to achieve timely progress ( Su et al., 2021a ; Su et al., 2021b ).

Current financial service providers, such as banks and insurance companies, are being challenged by digital finance. Because of the growing competition from FinTech companies, the latter provides unique prospects for employers to contact their younger and more innovative technological clientele ( Arner et al., 2015 ; Joshi, 2020 ; Wang et al., 2021 ). Against this background, there is an ongoing discussion on traditional financial intermediaries about handling FinTechs and whether competitive approaches acquisitions and alternatively engaging those firms as service providers that are compatible with their business models, for e.g., Lai (2020) ; Suprun et al. (2020) ; Vučinić, 2020 . The new opportunities presented by technology allow them to maintain their competitiveness and provide new and attractive services to their clients.

The study of Abbas et al., 2019d proved that highly innovative firms exhibited a propensity for building a business network to achieve sustainable performance. Furthermore, the findings indicated that firms achieving sustained performance did so by applying effective business networks and flexible capacities. The study’s results suggest that it presented a holistic and systematic approach for achieving sustainable performance through the dynamic capacities of businesses.

This study thus contributes to the actual literature by studying the linkage between digital finance and fintech. The bibliometric study data are represented in the overall research work on Digital Finance and FinTech in the ScienceDirect database. These data covered the period from 2006 to 2020, where the focus was on data of recent studies completed, especially in the last 3 years (2018, 2019, and 2020). The following parts of this article are structured as follows: Section Research Method and Questions discusses the research method and research questions. Section Methods and Materials deals with the methods and materials. Section Results and Discussion lays out our results and discussion. Section Conclusion and Limitation presents the conclusion and suggestions.

Research Method and Questions

Research method.

The bibliometric analysis takes all kinds of illumination as a research goal and uses mathematical and statistical methods to study science and technology’s technological trends and development ( Moed, 2006 ; Zhang et al., 2021 ). Reference measurements have been used extensively to reveal research status and development trends in a field. They have an essential role for researchers to understand a particular research field in depth ( van Oorschot et al., 2018 ; Vatananan-Thesenvitz et al., 2019 ). Additionally, scientists also use bibliometric methods to systematically study in ScienceDirect database publications to uncover their past, present, and future, especially in recent years, there have been many valuable research findings of this kind. A bibliographic measurement approach was used to analyze all publications in the database.

The main goal of a bibliometric analysis was to collect and evaluate the available research relevant to the area of interest and to produce objective results that can be audited and reproduced over and over again. When it comes to research results, a bibliometric analysis is a rigorous methodological assessment with the goal of grouping existing works on the subject and assisting in the development of evidence-based guidelines for professionals working in the study field ( Kitchenham, 2004 ; Prinsen et al., 2018 ). A bibliometric analysis should also identify the state of the art about the research subject ( Levy and Ellis, 2006 ).

Financial technology and the newer “Fintech” topics are gaining further focus as the effect of digitalization on the financial services sector rises ( Nicoletti et al., 2017 ; Leong and Sung, 2018 ). When it comes to financial services, one of these is why there is a lot of dependence on information, and the other is that most procedures, such as trading on an online platform ( Karagiannaki et al., 2017 ). With new financing models made available, broad and significant digitization of the financial service providers and customers’ needs to occur to facilitate the value chain transformation that is taking place. The word “Fintech” is a contraction of “financial technology,” and Citicorp chairman John Reed most likely coined it in the early 1990s in the light of a newly formed “Smart Card Forum” ( Puschmann, 2017 ). In a digital age, fintech applications redefined today’s product-centered thinking to include emerging ecosystems. Individual channels can become redundant when financial service designers focus on hybrid and incompatible modes of interaction-based consumer operations ( Gill et al., 2015 ).

Research Questions

The actual study compares bibliometric analysis to other methodologies (meta-analysis and systematic review), specifically in digital finance and fintech research. The study’s purpose is tied to its motivation. We will identify its scope and research trends, which will help readers learn more about digital finance and fintech in the scientific community, and the justification and significance of this study’s analysis are obtained from two research topics: the future trends and issues in the literature review on digital finance and fintech.

The following two suggested research questions will help the study accomplish its goals, which are to offer academics and practitioners a systematic, categorized perspective of what has been generated in the literature on digital finance and fintech. According to the main problem, the first question is focused on providing an overall quantitative and longitudinal perspective of the works on this topic, and it is worded as follows:

RQ1. What changes have occurred in the literature on digital finance and fintech?

The following sub-questions were generated from the main question:

RQ1.1. What has been the most influential research, such as those published in ScienceDirect?

RQ1.2. Which important references had the most impact on the studies that were identified?

RQ1.3. Which journals are the most widely read on this topic, and how has the number of publications changed over time?

To find the existing literature to build and develop new studies, a categorization of the key topics and research questions was used to classify the digital finance and fintech activities identified in published materials from the sample into several categories. As a result, the following is the formulation of the second question of this work:

RQ2. What are the most important topics and problems discussed in the scholarly literature on digital finance and fintech?

This section explains the procedure that was followed to complete this bibliometric literature evaluation using a technique that was previously established and verified. Furthermore, bibliometric analysis methods were used to determine the scenario state of the scientific literature on digital finance and fintech ( Ikpaahindi, 1985 ).

Methods and Materials

Bibliometric data.

The quantitative method “bibliometrics” ( Fairthorne, 1969 ; Pritchard, 1969 ) is one of the most quantitative measures used in evaluating literature. Bibliometric forms have been prevalent in digital finance, but few studies have considered them—nonetheless, citations connected to the concept of payments, protection, deposit, and retail provisioning. Fintech trends have been overlooked in publications. Looking at fintech-related metadata and the publications they connected to, the metadata gives us various viewpoints on each publication series.

The bibliometric study data are represented in the overall research work (in title, abstract, and author keywords for the article) on Digital Finance and FinTech in the ScienceDirect database. These data covered the period from 2006 to 2020, where the focus was on data of recent studies completed, especially in the last 3 years (2018, 2019, and 2020).

Study Methods and Tools

Many researchers ( Hood and Wilson, 2001 ; Osareh, 1996a ; Osareh, 1996b ; Tsay, 2005 ) have identified three key bibliometric rules. The first and earliest of these, according to Hood and Wilson (2001) , is Lotka’s law ( Lotka, 1926) which provides a relationship between authors and articles. Bradford’s law ( Bradford, 1934) deals with scattering articles on a scientific subject through scientific journals. Zipf’s law ( Zipf, 1949) is interested in the concept of frequency or occurrences.

The bibliometric study data represent the overall research on “Digital Finance and FinTech” in the ScienceDirect database. These data covered the period from 2006–2020. In which, we expected the use of Digital Finance and FinTech because of the closure and quarantine procedures during the epidemic. Therefore, articles from the ScienceDirect database that included fintech keywords in the title, abstract, and author keywords were reviewed and analyzed. Through review articles that were published starting in 2006 and also the literature from 2006 to 2020, the articles were reviewed and analyzed.

According to the processes and approaches used in bibliometric analysis, citation, co-citation, bib. coupling, co-author were analyzed for keywords, for e.g., Zupic and Čater, 2015 . The study relied on the citation indicator to find out the main keywords that studies focused on and prominent authors in Digital Finance and FinTech. To determine the network of research relationships between them, the practical stages of preparing the bibliometric study was carried out (study design, data collection, analysis, presentation, and guide); see Lobato et al. (2021 ).

Following the methodology of preparing the bibliometric study in management and organization, which is explained by Zupic and Čater (2015 ), the bibliometric analysis was carried out by completing the following steps: research design, study questions, and analysis approach selection (co-occurrence, publication, citation, and co-authorship), bibliometric data compilation, selection, and filtration, analysis (choose the appropriate bibliometric software, clean the data, and generate networks), visualization, and interpretation.

Results and Discussion

Descriptive of bibliometric data.

Analysts must provide complete knowledge regarding ongoing investigations in their respective fields and scholars that contribute to the analysis. These data change with time. Every day, fresh pieces of knowledge are introduced to the systems due to the advancement of new technology and new research. The usage of mathematical techniques to analyze articles, books, magazines, and other publications is bibliometric analysis. Geographic research, top writers, affiliations, colleges, documents, year-by-year articles, and citation analysis are all included in this report. The literature in this article was collected using the ScienceDirect database. Several networks have created keyword-based and titles in Digital Finance and FinTech science, sources, and authors.

To select the articles for final review, we used a three-step process. First, we collected and stored research articles (research articles, review articles, book chapters, and others) for the specified search keywords in the ScienceDirect databases, with an open beginning period to include as many publications as practical up to December 31, 2020. A total of 343 titles were retrieved during the first search. The article title, authors’ names and affiliations, abstract, keywords, and references were all included in the search results, which were downloaded in a CSV format.

We retrieved published research via a topic search of Digital Finance and FinTech of the ScienceDirect database on January 01, 2020. The following search terms were used: topic = (“Digital Finance” or “e-Finance” or “FinTech” Or “Fintech”), in title-abs-key from 2006 to 2020, and we got 343 studies (184 research articles and 14 review articles; 111 book chapters, 02 encyclopedias, 02 case reports, and 32 others) distributed over 15 years, as shown in Table 1 . The database used in bibliometric analysis or previous studies in a topic of digital finance and FinTech is described here, using numerical expressions (descriptive statistics).

TABLE 1 . Statistics of previous studies.

Identifying various contributing publications may enable the identification of the most relevant journal outlets in each area. The various publishing ports are shown in Table 1 . According to the number of published articles, research articles contribute the most, while book chapters rank second. Table 1 shows that the topics of digital finance, FinTech, and e-finance constitute a modern knowledge field, especially since most studies have been completed in the last 3 years (2018, 2019, and 2020). Moreover, most of these studies are research articles or book chapters; this explains the abundance of production in this type of research, which can be clearly shown in the following figure.

Figure 1 shows that most of the research has been performed in recent years: 155 in 2018, 88 in 2019, and 71 in 2020. Why is the curve appearing to rise, indicating the novelty of digital finance and financial technology as an area of knowledge in the financial management discipline?

FIGURE 1 . Publications per year.

For this research, the ScienceDirect database with all types of already published and unpublished publications is considered. There are many types of publications such as articles, journals, conference papers, and book chapters in a database. When researching for FinTech regulations, publication types that formed the majority were articles and conference papers and very few research studies were published in notes, conference reviews, and letters. When the results from the query were analyzed, all kinds of publications were articles, magazines, conference reviews, book chapters, etc. From 2006–2020, the trend has been increasing since 2006 and is being researched and explored more and more. Below line graph shows this trend:

Figure 2 shows that most studies used the following keywords: Fintech, blockchain, financial inclusion, bitcoin, banking, big data, etc.; this indicates that the previous studies used focus on the topic of digital finance and fintech.

FIGURE 2 . Publications per keyword.

In the last 3 years, it appears that the most prominent researchers in the area of digital finance and fintech are John Hill and David Lee Kuo Chuen; any researcher should refer to these in this specialty Figure 3.

FIGURE 3 . Publications per author.

Bibliometric Analysis and Networks

Items: 42 / Clusters: 8 / Links: 194 / Total link strength: 636.

It is noted from the Figure 4A,B that there are 8 clusters in the network that the researcher can take in the field of digital finance and FinTech as research thematic namely Fintech and its related clusters, financial inclusion and blockchain, cryptocurrency and bitcoin, financial services, entrepreneurial finance, P2P lending, distributed ledger technology, and trust.

The researcher should delve deeper into fintech, blockchain, financial inclusion, cryptocurrency, and bitcoin, as shown in the density and the following table in all these areas.

FIGURE 4 . (A) Network of keywords. (B) Density of keywords.

The most common terms used in previous studies were fintech, blockchain, financial inclusion, cryptocurrencies, financial services, and bitcoin. These should be concerned with the research and analysis of researchers in digital finance and FinTech. Now, we come to examine the most visible researchers in this field Table 2 .

TABLE 2 . Occurrence of keywords in the network.

It appears in the Figures 5A,B that the primary researcher in the area of digital finance and FinTech to which all other researchers are related is David Lee Kuo Chuen, and this should return all researchers to his research because of its importance in the field which was similar to the following study: Chuen (2015) , Chuen and Deng (2017) , Nian and Chuen (2015) , and Chuen et al. (2017) .

FIGURE 5 . (A) Network of authors. (B) Density of authors.

There too, John Hill’s research has not been widely used by other researchers, so we find that his name did not appear on the network and the density. The results of the following table show this.

The Table 3 results show that the most visible researcher in digital finance and FinTech is John Hill, especially his research ( Hill, 2018 ). Still, his research is not used by other researchers who are more visible in this field. On this basis, we can say that the study of David Lee Kuo Chuen is more influential than the research of John Hill in this field; this does not negate the return to his research but must refer to it because of its great importance in this field.

TABLE 3 . Occurrence of authors in the network.

Conclusion and Limitation

This article aims to explain digital finance and financial technology (Fintech), two distinct trends imposed in these areas. The second part of this article uses bolometric analysis with the ScienceDirect database to determine research progress in the field. This reveals that these superpowers are also driving research on the topic, with the most significant digital finance and financial technology publications, and FinTech is emerging on the market ( Omarova, 2021 ). We highlighted specific aspects that need further discussion based on the bibliometric analyses of the research focused on implementing FinTech and digital finance and its application disciplines. The methodologies and new main study topics are all discussed in the published studies.

Bibliometric analyses are a well-established method of meta-analytical investigation ( Paul and Criado, 2020 ) or so-called “meta-reviewed” of the literary world. Bibliometric analyses reveal key articles and explain critically if and within articles relate to any study subject or analyze how many other articles have been cited by one another. Finally, these analyses will assess the success of individual writers and their publications and their effect. The bibliometric citation analysis thus enables the meta-analytical evaluation of the history of a particular area or discipline and the identification of main strands and theoretical frameworks.

The analysis suggests a fundamental unit of study. It, therefore, goes farther than a single count of publications to cover impact centers and maps of relations between articles in a particular field of science ( Kim and McMillan, 2008 ; McKiernan et al., 2019 ). The meta-analysis of quotations thus represents the utility of the literature in other similar researchers ( Timulak, 2009 ). The bibliometric cycle review approach is an appropriate meta-analytic instrument for improving the three research objectives described previously. It provides insights into the research area of digital finance and the pattern of correlations in the Fintech industry.

This research will assist scholars and financial policymakers who are interested in digital finance in understanding the current state of Fintech needs and identifying trends in the corporate boardroom. It also supports the emerging acknowledgment that Fintech will play a critical element in the world endeavor to achieve digital financial trends, which is outlined in this research. Furthermore, digital finance and Fintech publications develop with the regularity, the multidisciplinary nature of digital finance, and the high-disciplinary individual’s inclusions. The high- or low-quality literature around digital finance is getting better, and individuals are involved.

The findings of this study can help the digital finance and Fintech industries develop policies and processes to enhance the emerging digital finance trends in the future. Financial and non-financial institutions can directly assess the financing process as strategic dimensions and policy makers’ vision.

Limitations of Research

This study has some methodological limitations, which may be addressed in future research. First, this research analyzed one database, ScienceDirect, which limited research in articles; other databases, such as Web of Science or Scopus, may be suggested in future bibliometric analyses. Second, it may envision future research from the source or topic of the publications, which may help develop a more comprehensive perspective on financial technology and digital finance.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.

Author Contributions

The author confirms being the sole contributor of this work and has approved it for publication.

Conflict of Interest

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The author extends his appreciation to the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia, to fund this research work through the project number UB-56-1442.

Abbas, J., Aman, J., Nurunnabi, M., and Bano, S. (2019b). The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan. Sustainability 11 (6), 1683. doi:10.3390/su11061683

CrossRef Full Text | Google Scholar

Abbas, J., Hussain, I., Hussain, S., Akram, S., Shaheen, I., and Niu, B. (2019a). The Impact of Knowledge Sharing and Innovation upon Sustainable Performance in Islamic Banks: A Mediation Analysis through an SEM Approach. Sustainability 11 (15), 4049. doi:10.3390/su11154049

Abbas, J., Mahmood, S., Ali, H., Raza, M., Ali, G., Aman, J., et al. (2019c). The Effects of Corporate Social Responsibility Practices and Environmental Factors through a Moderating Role of Social Media Marketing on Sustainable Performance of Firms' Operating in Multan, Pakistan. Sustainability 11 (12), 3434. doi:10.3390/su11123434

Abbas, J., Raza, S., Nurunnabi, M., Minai, M. S., and Bano, S. (2019d). The Impact of Entrepreneurial Business Networks on Firms' Performance through a Mediating Role of Dynamic Capabilities. Sustainability 11 (11), 3006. doi:10.3390/su11113006

Abbas, J., Zhang, Q., Hussain, I., Akram, S., Afaq, A., and Shad, M. A. (2020). Sustainable Innovation in Small Medium Enterprises: the Impact of Knowledge Management on Organizational Innovation through a Mediation Analysis by Using SEM Approach. Sustainability 12 (6), 2407. doi:10.3390/su12062407

Anjum, M. N., Xiuchun, B., Abbas, J., Shuguang, Z., and McMillan, D. (2017). Analyzing Predictors of Customer Satisfaction and Assessment of Retail Banking Problems in Pakistan. Cogent Business Manag. 4 (1), 1338842. doi:10.1080/23311975.2017.1338842

Arner, D. W., Barberis, J., and Buckley, R. P. (2015). The Evolution of Fintech: A New post-crisis Paradigm. Geo. J. Int'l L. 47, 1271. doi:10.2139/ssrn.2676553

Azizi, M. R., Atlasi, R., Ziapour, A., Abbas, J., and Naemi, R. (2021). Innovative Human Resource Management Strategies during the COVID-19 Pandemic: A Systematic Narrative Review Approach. Heliyon 7, e07233. doi:10.1016/j.heliyon.2021.e07233

Barras, R. (1990). Interactive Innovation in Financial and Business Services: The Vanguard of the Service Revolution. Res. Pol. 19 (3), 215–237. doi:10.1016/0048-7333(90)90037-7

Bradford, S. C. (1934). Sources of Information on Specific Subjects. Engineering 137, 85–86.

Google Scholar

Brandl, B., and Hornuf, L. (2020). Where Did FinTechs Come from, and where Do They Go? the Transformation of the Financial Industry in Germany after Digitalization. Front. Artif. Intell. 3, 8. doi:10.3389/frai.2020.00008

Chuen, D. L. K., and Deng, R. H. (2017). Handbook of Blockchain, Digital Finance, and Inclusion: Cryptocurrency, Fintech, Insurtech, Regulation, Chinatech, mobile Security, and Distributed Ledger . London, UK: Elsevier .

Chuen, D. L. K. (2015). Handbook of Digital Currency: Bitcoin, Innovation, Financial Instruments, and Big Data London, UK: Academic Press .

Fairthorne, R. A. (1969). Empirical Hyperbolic Distributions (Bradford‐Zipf‐Mandelbrot) for Bibliometric Description and Prediction. J. documentation 25 (4), 319–343. doi:10.1108/eb026481

Gill, A., Bunker, D., and Seltsikas, P. (2015). Moving Forward: Emerging Themes in Financial Services Technologies’ Adoption. Commun. Assoc. Inf. Syst. 36 (1), 12. doi:10.17705/1cais.03612

Gomber, P., Koch, J.-A., and Siering, M. (2017). Digital Finance and FinTech: Current Research and Future Research Directions. J. Bus Econ. 87 (5), 537–580. doi:10.1007/s11573-017-0852-x

Hill, J. (2018). Fintech and the Remaking of Financial Institutions . UK: Elsevier .

Hood, W. W., and Wilson, C. S. (2001). The Literature of Bibliometrics, Scientometrics, and Informetrics. Scientometrics 52 (2), 291–314. doi:10.1023/a:1017919924342

Ikpaahindi, L. (1985). An Overview of Bibliometrics: its Measurements, Laws and Their Applications. Libri 35, 163.

Joshi, V. C. (2020). Digital Finance, Bits and Bytes . Singapore: Springer .

Kanungo, R. P., and Gupta, S. (2021). Financial Inclusion through Digitalisation of Services for Well-Being. Technol. Forecast. Soc. Change 167, 120721. doi:10.1016/j.techfore.2021.120721

Karagiannaki, A., Vergados, G., and Fouskas, K. (2017). “The Impact of Digital Transformation in the Financial Services Industry: Insights From an Open Innovation Initiative in Fintech in Greece.,” in Mediterranean Conference on Information Proceedings 2. (MICS) , Genoa, Italy . Available at: http://aisel.aisnet.org/mcis2017/2

Kim, J., and McMillan, S. J. (2008). Evaluation of Internet Advertising Research: A Bibliometric Analysis of Citations from Key Sources. J. Advertising 37 (1), 99–112. doi:10.2753/joa0091-3367370108

Kitchenham, B. (2004). Procedures for Performing Systematic Reviews . Keele, UK: Keele University .

Kuo Chuen, D. L., Guo, L., and Wang, Y. (2017). Cryptocurrency: A New Investment Opportunity? Jai 20 (3), 16–40. doi:10.3905/jai.2018.20.3.016

Lai, K. P. (2020). “FinTech: The Dis/Re-Intermediation of Finance?,” in The Routledge Handbook of Financial Geography . London, UK: Routledge , 440–457. doi:10.4324/9781351119061-24

Lebni, J. Y., Toghroli, R., Abbas, J., NeJhaddadgar, N., Salahshoor, M. R., Mansourian, M., et al. (2020). January 1, 2020). A Study of Internet Addiction and its Effects on Mental Health: A Study Based on Iranian University Students [Original Article]. J. Educ. Health Promot. 9 (1), 205. doi:10.4103/jehp.jehp_148_20

Legner, C., Eymann, T., Hess, T., Matt, C., Böhmann, T., Drews, P., et al. (2017). Digitalization: Opportunity and challenge for the Business and Information Systems Engineering Community. Business Inf. Syst. Eng. 59 (4), 301–308. doi:10.1007/s12599-017-0484-2

Leong, K., and Sung, A. (2018). FinTech (Financial Technology): what Is it and How to Use Technologies to Create Business Value in Fintech Way? Int. J. Innovation, Manag. Techn. 9 (2), 74–78. doi:10.18178/ijimt.2018.9.2.791

Levy, Y., and Ellis, T. J. (2006). A Systems Approach to Conduct an Effective Literature Review in Support of Information Systems Research. Informing Science 9. doi:10.28945/479

Liu, F., Wang, D., Duan, K., and Mubeen, R. (2021). Social media Efficacy in Crisis Management: Effectiveness of Non-pharmaceutical Interventions to Manage the COVID-19 Challenges [Original Research]. Front. Psychiatry 12 (1099), 626134. doi:10.3389/fpsyt.2021.626134

Lobato, C. G., Cristino, T. M., Faria Neto, A., and Costa, A. F. B. (2021). Lean System: Analysis of Scientific Literature and Identification of Barriers for Implementation from a Bibliometric Study. Gestão & Produção 28 (1), 1–26. doi:10.1590/1806-9649.2020v28e4769

Lotka, A. J. (1926). The Frequency Distribution of Scientific Productivity. J. Wash. Acad. Sci. 16 (12), 317–323.

McKiernan, E. C., Schimanski, L. A., Nieves, C. M., Matthias, L., Niles, M. T., and Alperin, J. P. (2019). Meta-research: Use of the Journal Impact Factor in Academic Review, Promotion, and Tenure Evaluations. Elife 8, e47338. doi:10.7554/eLife.47338

Moed, H. F. (2006). Citation Analysis in Research Evaluation . Netherlands: Springer Science & Business Media .

Nian, L. P., and Chuen, D. L. K. (2015). “Introduction to Bitcoin,” in Handbook of Digital Currency (London, UK: Academic Press ), 5–30. doi:10.1016/b978-0-12-802117-0.00001-1

Nicoletti, B., Nicoletti, W., and Weis, (2017). Future of FinTech . Basingstoke, UK: Palgrave Macmillan .

Omarova, S. T. (2021). “Fintech and the Limits of Financial Regulation: A systemic perspective,” in Routledge Handbook of Financial Technology and Law . London, UK: Routledge 44–61.

Osareh, F. (1996a). Bibliometrics, Citation Analysis and Co-Citation Analysis: A Review of Literature I. Libri 46 (3), 149–158. doi:10.1515/libr.1996.46.3.149

Osareh, F. (1996). Bibliometrics, Citation Anatysis and Co-Citation Analysis: A Review of Literature II. Ann. Phys. 46 (4), 217–225. doi:10.1515/libr.1996.46.4.217

Ozili, P. K. (2018). Impact of Digital Finance on Financial Inclusion and Stability. Borsa Istanbul Rev. 18 (4), 329–340. doi:10.1016/j.bir.2017.12.003

Paul, J., and Criado, A. R. (2020). The Art of Writing Literature Review: What Do We Know and what Do We Need to Know? Int. Business Rev. 29 (4), 101717. doi:10.1016/j.ibusrev.2020.101717

Prinsen, C. A., Mokkink, L. B., Bouter, L. M., Alonso, J., Patrick, D. L., De Vet, H. C., et al. (2018). COSMIN Guideline for Systematic Reviews of Patient-Reported Outcome Measures. Qual. Life Res. 27 (5), 1147–1157. doi:10.1007/s11136-018-1798-3

Pritchard, A. (1969). Statistical Bibliography or Bibliometrics. J. documentation 25 (4), 348–349.

Puschmann, T. (2017). Fintech. Business Inf. Syst. Eng. 59 (1), 69–76. doi:10.1007/s12599-017-0464-6

Su, Z., McDonnell, D., Cheshmehzangi, A., Li, X., and Cai, Y. (2021a). The Promise and Perils of Unit 731 Data to advance COVID-19 Research. BMJ Glob. Health 6 (5), e004772. doi:10.1136/bmjgh-2020-004772

Su, Z., McDonnell, D., Wen, J., Kozak, M., Šegalo, S., Xiang, L., et al. (2021b). Mental Health Consequences of COVID-19 media Coverage: the Need for Effective Crisis Communication Practices. Globalization and Health 17 (1), 4. doi:10.1186/s12992-020-00654-4

Suprun, A., Petrishina, T., and Vasylchuk, I. (2020). “Competition and Cooperation between Fintech Companies and Traditional Financial Institutions,” in E3S Web of Conferences , Ukraine , April 22, 2000 . Available at: https://doi.org/10.1051/e3sconf/202016613028 . doi:10.1051/e3sconf/202016613028

Teece, D. J. (2010). Business Models, Business Strategy and Innovation. Long range Plann. 43 (2-3), 172–194. doi:10.1016/j.lrp.2009.07.003

Timulak, L. (2009). Meta-analysis of Qualitative Studies: A Tool for Reviewing Qualitative Research Findings in Psychotherapy. Psychotherapy Res. 19 (4-5), 591–600. doi:10.1080/10503300802477989

PubMed Abstract | CrossRef Full Text | Google Scholar

Tsay, R. S. (2005). Analysis of Financial Time Series . Hoboken, NJ: John wiley and sons .

van Oorschot, J. A., Hofman, E., and Halman, J. I. (2018). A Bibliometric Review of the Innovation Adoption Literature. Technol. Forecast. Soc. Change 134, 1–21. doi:10.1016/j.techfore.2018.04.032

Varga, D. (2017). Fintech, the new era of Financial Services. Vezetéstudomįny-Budapest Manag. Rev. 48 (11), 22–32. doi:10.14267/veztud.2017.11.03

Vatananan-Thesenvitz, R., Schaller, A. A., and Shannon, R. (2019). A Bibliometric Review of the Knowledge Base for Innovation in Sustainable Development. Sustainability 11 (20), 5783. doi:10.3390/su11205783

Vučinić, M. (2020). Fintech and Financial Stability Potential Influence of FinTech on Financial Stability, Risks and Benefits. J. Cent. Banking Theor. Pract. 9 (2), 43–66. doi:10.2478/jcbtp-2020-0013

Wang, C., Wang, D., Abbas, J., Duan, K., and Mubeen, R. (2021). 2021-September-03)Global Financial Crisis, Smart Lockdown Strategies, and the COVID-19 Spillover Impacts: A Global Perspective Implications from Southeast Asia [Original Research]. Front. Psychiatry 12 (1099), 643783. doi:10.3389/fpsyt.2021.643783

Zhang, J., Jiang, L., Liu, Z., Li, Y., Liu, K., Fang, R., et al. (2021). A Bibliometric and Visual Analysis of Indoor Occupation Environmental Health Risks: Development, Hotspots and Trend Directions. J. Clean. Prod. 300, 126824. doi:10.1016/j.jclepro.2021.126824

Zipf, G. K. (1949). Human Behavior and the Principle of Least Effort: An Introd. To Human Ecology .

Zupic, I., and Čater, T. (2015). Bibliometric Methods in Management and Organisation. Organizational Res. Methods 18 (3), 429–472. doi:10.1177/1094428114562629

Keywords: digital finance, fintech, bibliometric analysis, ScienceDirect database, e-finance

Citation: Brika SKM (2022) A Bibliometric Analysis of Fintech Trends and Digital Finance. Front. Environ. Sci. 9:796495. doi: 10.3389/fenvs.2021.796495

Received: 16 October 2021; Accepted: 14 December 2021; Published: 10 January 2022.

Reviewed by:

Copyright © 2022 Brika. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Said Khalfa Mokhtar Brika, [email protected]

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In recent years, the world of finance has undergone a significant transformation thanks to the rise of Financial Technology , or Fintech. Fintech refers to the innovative use of technology to provide financial services in a more efficient, accessible, and user-friendly manner. From mobile payment apps to robo-advisors, Fintech solutions have revolutionized how individuals and businesses manage their finances.

McKinsey's research underscores the rapid expansion of fintech, evident in the United States where nearly half of consumers utilized fintech products in 2021, notably peer-to-peer payment services and nonbank transfers. Moreover, McKinsey notes a significant surge in capital raised by fintech firms during the latter half of the 2010s, with venture capital funding escalating from $ 19.4 billion in 2015 to $33.3 billion by 2020 .

The advent of financial technology, or fintech, has heralded a significant shift in how consumers manage their finances, with a remarkable surge in adoption rates worldwide. According to recent statistics, a staggering 48% of Americans and an even higher 84% of UK respondents utilize fintech on a daily basis. This surge isn't limited to specific income brackets either. At the same time, in 2020, fintech adoption was more pronounced among higher earners. By 2022, rates had converged at around 80% across various income spectrums according, to key findings sourced by Arounda . One of the most notable aspects of fintech adoption is its near-equal usage among genders, with 82% of men and 78% of women embracing these digital financial solutions.

How Fintech Serves As A Force For Equality

In the face of ongoing economic uncertainties, fintech continues to play a pivotal role in assisting consumers in managing their finances more effectively. From clarifying spending patterns to facilitating efficient budgeting, providing instant digital access, and tracking progress towards financial goals, fintech offers a multitude of benefits that help consumers navigate turbulent times with greater resilience.

Moreover, fintech isn't just about individual financial management; it also serves as a force for equality, promoting inclusion and accessibility in the financial realm. Fintech startups like Fintech Farm are leading the charge by leveraging technology to create digital banks in emerging markets, thereby expanding access to financial services and driving financial inclusion . Neobanks like Fintech Farm differentiate themselves with innovative features; for instance, their shaking-based money transfer function on the Fibo app eliminates the need for cumbersome account details or phone numbers, simplifying transactions for users.

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The total $40 million funding secured by Fintech Farm underscores the growing interest and investment in fintech startups, particularly those focused on digital banking solutions. These innovative ventures, often referred to as neobanks or challenger banks, are disrupting traditional banking models and democratizing financial services.

Pioneering the Future: Fintech's Evolution Beyond Digital Transactions

In the annals of fintech history, success stories like Monobank stand as testaments to the transformative power of innovation. Within just a few years of operation, this Ukrainian neobank has garnered over 4.5 million customers and generated more than $100 million in operating income . Backed by visionary leaders like Dmytro Dubilet, Monobank's meteoric rise serves as a beacon of inspiration, demonstrating the boundless possibilities within the fintech realm.

However, fintech's impact transcends mere numbers; it represents a seismic shift in the financial landscape. Beyond being a mere technological trend, fintech emerges as a transformative force, reshaping the very fabric of finance. By equipping consumers with cutting-edge digital solutions and championing financial inclusion, fintech spearheads positive change, forging a path toward a more equitable and accessible financial future.

Companies like Stripe, Mercury, and Fintech Farm are leading the charge in this revolution and are shaping the new financial landscape for today's consumers. Dmytro Dubilet, the founder of Fintech Farm, envisions a future where banking transcends mere transactions, transforming into a comprehensive experience driven by social connectivity and technological innovation.

Central to Fintech Farm's ethos is the commitment to providing not just an exceptional mobile app but an entire end-to-end tech stack that revolutionizes the banking experience. From developing cutting-edge credit engines and AI-powered credit models to implementing data-driven customer acquisition and retention strategies, Fintech Farm embodies the essence of fintech's transformative potential.

Dubilet emphasizes the importance of creating a banking experience that goes beyond mere utility, aiming to foster genuine affection and loyalty among customers. For Fintech Farm, it's not enough for customers to merely use their bank; they strive to create an environment where customers truly love their bank—an ambition underscored by their relentless pursuit of excellence in customer service and innovation.

Fintech Beyond Digital Transactions

In essence, Fintech Farm exemplifies the evolution of fintech beyond digital transactions pioneering a future where banking is not just about financial transactions, but about building meaningful connections and empowering individuals to thrive in an ever-evolving digital landscape. As fintech continues to evolve and innovate, Fintech Farm stands as a beacon of progress, leading the charge toward a future where finance is not just accessible but truly transformative.

Empowering Financial Inclusion

The trajectory points to finance blending more seamlessly into digital lifestyles. In the coming decade, innovations like social connectivity may gradually redefine banking. But balancing novelty with pragmatic fundamentals could determine which startups disrupt traditional strongholds versus fading as passing fads.

One of the most promising aspects of Fintech is its potential to promote financial inclusion by providing services to underserved populations such as Nigeria, Vietnam, India, and more. In many parts of the world, traditional banking services are either unavailable or prohibitively expensive. Fintech startups leverage technology to reach these populations and offer them access to basic financial services such as savings accounts, loans, and insurance.

Five Ways Consumers Can Benefit from Fintech

Enhanced Accessibility : Fintech platforms break down traditional barriers to financial services, providing access to banking and investment opportunities for previously underserved or excluded individuals.
Cost Savings : Fintech solutions often offer lower fees and competitive rates compared to traditional financial institutions, resulting in more affordable banking and investment options for consumers.
Streamlined Financial Management : Fintech tools empower consumers with powerful tools to manage their finances more efficiently, from budgeting apps that track expenses to robo-advisors that automate investment strategies.
Personalized Financial Services : Fintech companies leverage data analytics and artificial intelligence to deliver personalized financial services tailored to individual needs and preferences, enhancing the overall customer experience.
Innovative Payment Solutions : Fintech has revolutionized the way consumers transact, offering innovative payment solutions that are faster, more convenient, and more secure than ever before. These solutions simplify transactions and enhance security.

In essence, fintech empowers consumers with enhanced accessibility, cost savings, streamlined financial management, personalized services, and innovative payment solutions, ultimately enabling them to take control of their finances and achieve their financial goals more efficiently and effectively.

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Fintech: A content analysis of the finance and information systems literature

Research Paper
Published: 03 April 2023
Volume 33 , article number 2 , ( 2023 )

Cite this article

Zack Jourdan 1 ,
J. Ken. Corley 2 ,
Randall Valentine 3 &
Arthur M. Tran 3

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The amount of research related to financial technologies (fintech) has grown rapidly since these modalities have been implemented. A review of this literature base will help identify the topics that have been explored and identify topics for further research. This research project collects, synthesizes, and analyzes both the research strategies (i.e., methodologies) and content (e.g., topics, focus, categories) of the literature, and then discusses an agenda for future research efforts. We searched for fintech research published in the last 20 years and analyzed 146 articles published in Finance and 70 articles published in Information Systems (IS) during this period in their respective A*, A, and B journals in the 2019 Australian Business Deans Council list. We found an increasing level of activity during the most recent 6-year period and a biased distribution of fintech articles focused on exploratory methodologies. We also found several research strategies that were either underrepresented or absent from the pool of fintech research and identified several subject areas that need further exploration. We also created four fintech topic categories to organize and classify this diverse research stream.

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Introduction

With the continuous advancements in technology, the current interest in fintech in both academia and in practice is more prevalent than ever. Typically, a portmanteau for “financial technology”, fintech has been referenced for more than 40 years in more than 200 scholarly articles (Schueffel, 2016 ). Throughout the years, different definitions of fintech have been proposed for different contexts and across countries, while the origin of the term “fintech” remains to be a point of contention. Only until recently, Schueffel ( 2016 ) reconciles various existing definitions and defines fintech as “a new financial industry that applies technology to improve financial activities.” As a joint evolution of finance and technology, fintech encompasses cryptocurrencies, Internet banking, mobile payments, crowdfunding, peer-to-peer lending, Robo-Advisory, online identification, and many other important innovations (Lagna & Ravishankar, 2022 ). Nonetheless, fintech is still a relatively undiscovered academic field and expects its definition to continue to evolve. To date, no study has examined neither the methodologies employed nor the content thereof. The purpose of this study is to synthesize the methodologies and content of all fintech article from the past 20 year encompassing all journals on the Australian Business Deans list that have a rating of A*, A, and B. In doing so, we hope to find a synthesis of keywords and methodological advances that can be used in further exploration of fintech research.

Studies which systematically review the literature, such as Farooq and Jibran ( 2018 ), have been shown to be valuable contributions to understanding the scope, measurements, impact size, and determinants of a particular area to synthesize with the area’s future research agenda. In this paper, we performed a meta-analysis of research methods employed in the data stream of fintech research. In the literature stream, there has not been a comprehensive survey of the methodologies employed in fintech literature. In fact, there have been very few studies reviewing the methodologies employed in finance research in the past 15 years, with Kim and Ji ( 2015 ) and Adams et al. ( 2019 ) being the closest examples. Lagna and Ravishankar ( 2022 ) illustrated the growing interest that IS researchers have shown in the fintech research domain. Alt et al. ( 2018 ) called fintech a revolution that had evolved from offline, hierarchical, process-oriented organizations to digital, agile, customer-centric system and stated, “FinTech businesses are more IT companies than financial providers were before.”

The following sections of the paper will examine the current literature to determine what is known about the concept of fintech. The remainder of this paper is organized as follows: a description of the methodology for the analysis of the fintech research is presented. This is followed by the results. Finally, the research is summarized with a discussion of the limitations of this project and suggestions for future research.

Literature review

One focus in the fintech literature is about how fintech companies provide new and improved financial services. As Thakor ( 1999 ) discusses, the development of information technology enables new financial firms to be highly specialized and provides products and services which are tailored to customer preferences. As new players in the financial market, fintech companies have the potential to reduce financial contracting frictions and increase consumer welfare (Philippon, 2015 ). For example, Fuster et al. ( 2019 ) find evidence that fintechs have improved the productivity of mortgage lending.

These additional values which fintechs may bring to the finance industry come from the fact that these firms are different from traditional financial institutions. Thakor ( 2020 ) discusses that fintech firms bare lower operating costs than traditional banks. For instance, Lending Club, a fintech firm, has operating costs as a percentage of outstanding loans at 2.70% compared to those of banks at almost 7%. According to Benoit et al. ( 2019 ), fintechs also have lower regulatory costs than banks. In the USA, even though peer-to-peer (P2P) lending is subject to the US Securities and Exchange Commission (SEC)’s regulation and state laws, these regulatory burdens are much lighter than that of banks.

Much of the recent fintech research is concerned with how fintechs impact traditional banks. Christensen ( 2016 ) provides the “disruptive theory” in which new entrants effectively compete with traditional players by providing accessible and cost-effective goods and services to customers. Boyd and De Nicolo ( 2005 ) posit that banks become more competitive by providing cheaper loans. In turn, borrowers have less incentive to risk shift which results in banks having less default risk. Similarly, Goetz ( 2018 ) finds that the increased competition forces banks to be more efficient by reducing over-lending and engaging in relationship lending. On the other hand, Bertsch et al. ( 2020 ) find that banks’ increased misconduct is related to the emergence of the US online lending market. Large banks can also choose to acquire fintech firms. For instance, in 2015, Capital One acquired Level Money to strengthen its capabilities in digital banking technologies (Li et al., 2017 ). Hornuf et al. ( 2021 ) find that many banks acknowledge the technical superiority of fintech start-ups and have incorporated these firms’ products and services into their own business models.

Thakor ( 2020 ) and other survey papers review the fintech literature’s research contents of what we currently know about fintech and the research directions that have been taken. On the other hand, this paper focuses on reviewing the research methodologies. Studies which systematically review the literature, such as Farooq and Jibran ( 2018 ), have been shown to be valuable contributions to understanding the scope, measurements, impact size, and determinants of a particular area in order to synthesize with the area’s future research agenda. There has not been a comprehensive survey of the methodologies employed in fintech literature. In fact, there have been very few studies reviewing the methodologies employed in finance research in the past 15 years, with Kim and Ji ( 2015 ) and Adams et al. ( 2019 ) being the closest examples.

For the purpose of reviewing the practice of significance testing, Kim and Ji ( 2015 ) survey recently published articles in four top-ranking finance journals. They find that finance researchers almost exclusively use the conventional significance levels (1%, 5%, and 10%) while paying little attention to the sample size, power of the test, and expected losses. The authors also suggest using more often the Bayesian method or revised standards for evidence (0.1% or 0.5%). Adams et al. ( 2019 ) review the articles published in the same four top-ranking finance journals from 1988 to 2017 in order to investigate whether outliers are treated appropriately in these studies. The authors document that each year, 30–70% of these articles use OLS. To encourage finance researchers to utilize other useful econometric methods, they propose a multivariate outlier identification strategy. As the authors explain, this technique can minimize frictions which hinder the adoption of these methods. Due to their purposes of addressing very specific problems, these two articles provide method surveys that are non-comprehensive. Table 1 summarizes the differences between this paper and the other surveys of fintech methods.

Methodology

The approach to the analysis of the fintech research is to first identify trends in the Finance and Information Systems (IS) literature because fintech is the intersection between financial services and information systems. Specifically, we wished to capture the trends pertaining to (1) the number and distribution of fintech articles published in the leading journals, (2) methodologies employed in fintech research, and (3) the research topics being published in this research. During the analysis of this literature, we attempted to identify gaps and needs in the research and therefore enumerate and discuss a research agenda which allows for the progression of research (Webster & Watson, 2002 ). Systematic literature reviews are a meta-analysis technique designed to collect, organize, analyze, and categorize existing knowledge and concepts in the research literature of a given category (Briner et al., 2009 ). In short, we hope to paint a representative landscape of the current fintech literature base to influence the direction of future research efforts in this important area of study.

To examine the current state of research on fintech in the top Finance and IS journals, the authors conducted a literature review and analysis in three phases. Phase 1 accumulated a representative pool of articles. Phase 2 classified the articles by research method. Phase 3 classified the research by topic. Each of the three phases is discussed in the following paragraphs.

Phase 1: Accumulation of article pool

We used the Web of Science (WoS) citation database, Scopus citation database, and Google Scholar to search for research articles with a focus on fintech. The search parameters were constrained based on (a) a list of top ranked journals, (b) a specific time range, and (c) key search terms. Figure 1 illustrates steps in the content analysis process adapted from Neuendorf ( 2002 ) and successfully employed by several similar research studies in Internet marketing (Corley et al., 2013 ), Business Intelligence (Jourdan et al., 2008 ), and Enterprise Resource Planning systems (Cumbie et al., 2005 ).

Overview of literature analysis

First, the researchers chose to use the journals from the Australian Business Dean’s Council ABDC list (ABDC, 2019 ). Then, we filtered the ranking of journals to include only Finance (Code 1502) and collected the list of A* (see Table 2 ), A (see Table 3 ), and B (see Table 4 ) journals. Then, we filtered the ranking of journals to include only Information Systems (Code 0806) and collected the list of A* (see Table 5 ), A (see Table 6 ), and B (see Table 7 ) journals. Many of the Finance and IS journals in the sample contained no fintech articles and were deleted from the tables.

The search parameters were further constrained to a specific timeframe. As previously discussed, the term fintech was first coined by Citicorp in 1993 (Schueffel, 2016 ). The search parameters were further constrained based on the historical timeframe in which technologies capable of facilitating the Finance function were first introduced, and the years of publications for articles in our search sample were constrained to the years of 2002 through December of 2021.

The final constraint was based on the key search term “fintech.” In WoS, Scopus, and Google Scholar the search engine scanned for the term “fintech” and close variations of this term found in the title, abstract, and keywords of articles published in the top Finance journals between January of 2002 and December of 2021 when the search was executed. There was a considerable overlap in the pool of articles returned from the three search engines (WoS, SCOPUS, and Google Scholar). Of the 322 (227 Finance and 95 IS) total articles in the initial search, 83 articles (67 Finance and 16 IS) were removed because the articles’ publication year was 2022. This further shows the explosive growth of this research topic’s popularity as the search was conducted in late February of 2022. Once duplicate entries and non-research articles (book reviews, editorials, commentary, etc.) were removed, another 26 (17 Finance and 9 IS) articles were removed. As a result of this process, 216 (146 Finance and 70 IS) articles remained in the composite data pool for analysis. All 216 article files were collected in Adobe Acrobat PDF format and loaded into NVivo 11 to run a word frequency query of the content without numbers and extemporaneous words (i.e. “a,” “and,” “the,” etc.). Figure 2 shows the word cloud that resulted from this query.

Word cloud of fintech research created in NVivo

Phase 2: Classification by research strategy

Once the researchers identified the articles for the final data pool, each article was examined and categorized according to its research strategy. Due to the subjective nature of research strategy classification, content analysis methods were used for the categorization process (Neuendorf, 2017 ).

First, the research categories were adopted from Scandura and Williams ( 2000 ) (see Table 8 ), who extended the research strategies initially described by McGrath ( 1982 ). Specifically, nine categories of business research strategies were selected including: Formal theory/literature reviews, sample survey, laboratory experiment, experimental simulation, field study (primary data), field study (secondary data), field experiment, judgment task, and computer simulation.

Second, to guard against the threats to reliability (Neuendorf, 2017 ), we performed a pilot test on articles not included in the final data pool for this study. Researchers independently categorized the articles in the pilot test based on the best fit among the nine research strategies. After all articles in the pilot test were categorized, the researchers compared their analyses. In instances where the independent categorizations did not match, the researchers re-evaluated the article collaboratively by reviewing the research category definitions, discussing the disagreement thoroughly, and collaboratively assigning the article to a single category. This process allowed the researchers to develop a collaborative interpretation of the research category definitions. This pilot test served as a training session for accurately categorizing the articles for this study.

Each research strategy is defined by a specific design approach, and each is also associated with certain tradeoffs that researchers must make when designing a study. These tradeoffs are inherent flaws that limit the conclusions that can be drawn from a particular research strategy. These tradeoffs refer to three aspects of a study that can vary depending on the research strategy employed. These variable aspects include generalizability from the sample to the target population (external validity), precision in measurement and control of behavioral variables (internal and construct validity), and the issue of realism of context (Scandura & Williams, 2000 ).

Campbell and Cook ( 1976 ) stated that a study has generalizability when the study has external validity across times, settings, and individuals. Formal theory/literature reviews and sample surveys have a high degree of generalizability by establishing the relationship between two constructs and illustrating that this relationship has external validity. A research strategy that has low external validity, but high internal validity is a benefit of the laboratory experiment. In the laboratory experiment, where the degree of measurement precision is high, cause and effect relationships may be determined, but these relationships may not be generalizable for other times, settings, and populations. While the formal theory/literature reviews and sample surveys have a high degree of generalizability and the laboratory experiment has a high degree of precision of measurement, these strategies have low degree of contextual realism. The only two strategies that maximize degree of contextual realism are field studies that use either primary or secondary data because the data is collected in an organizational setting (Scandura & Williams, 2000 ). The other four strategies maximize neither generalizability, nor degree of precision in measurement, nor degree of contextual realism. This point illustrates the futility of using only one strategy when conducting fintech research. Because no single strategy can maximize all types of validity, it is best for researchers to use a variety of research strategies.

Two coders independently reviewed and classified each article according to research strategy. Only a few articles were reviewed at one sitting to minimize coder fatigue and thus protect intercoder reliability (Neuendorf, 2017 ). Upon completion of the classification process, agreements and disagreements were tabulated. The percent agreement was 87.5% ( N = 216). Then, intercoder reliability ( κ = 0.874) using Cohen’s Kappa (Cohen, 1960 ) and Krippendorf’s Alpha (Krippendorff, 2013 ) for each methodology ( α = 0.859) was calculated. Neuendorf ( 2017 ) suggests that a Cohen’s kappa greater than 0.800 is considered acceptable. Krippendorff ( 2013 ) stated that researchers could use reliability scores greater than 0.800. Therefore, the calculations for intercoder reliability were well within the acceptable ranges. We calculated the reliability measures prior to discussing disagreements as mandated by Weber ( 1990 ). If the original reviewers did not agree on how a particular article was coded, a third reviewer arbitrated the discussion of how the disputed article was to be coded. This process resolved the disputes in all cases.

Phase 3: Categorization by fintech research topic

Typically, the process of categorizing research articles by a specific research topic involves an iterative cycle of brainstorming and discussion sessions among the researchers. This iterative process helps to identify common themes within the data pool of articles. Through the collaborative discussions during this process researchers can synthesize a hierarchical structure within the literature of overarching research topics and more granular level subtopics. The outcome is a better understanding of the current state of a particular stream of research. This iterative process was modified for this specific study on the topic of fintech.

This process resulted in four research topics: Enhance, Impact, Innovate, and Research. The Enhance topic was research that investigates how traditional financial products and services are implemented and improved by using fintech. Examples include using fintech to improve the traditional activities of making personal consumer loans (Di Maggio & Yao, 2021 ; Gerrans et al., 2021 ), analyzing the creditworthiness of borrowers (Jagtiani & Lemieux, 2019 ), and enhancing customer experience in traditional wealth management (Kim et al., 2020 ). The Impact topic analyses fintech’s influence on industries, governments, and economies and includes the impact of technology on banking industry misconduct (Bertsch et al., 2020 ), fragility of financial institutions that use various technologies (Fung et al., 2020 ), how various technologies are affecting the insurance industry (Stoeckli et al., 2018 ), and the new regulatory models necessary from fintech (Jiang et al., 2021 ). The Innovate topic explores financial products and services that were created by or made possible by the implementation of fintech with financial products and services such as blockchain, initial coin offerings (ICOs), and cryptocurrencies (Zhao et al., 2021 ), digital tokens (Benedetti & Nikbakht, 2021 ), peer to peer lending (Fu, Huang, & Singh, 2021), mobile payments (Du, 2018), crowdfunding (Lin & Pursiainen, 2021 ), and the analysis of the new business models created by innovations in fintech (Gomber, Kauffman, Parker, & Weber, 2018). The Research topic illustrates the importance and impact of fintech on individuals and society up to and including research on fintech itself. Research that represents this topic include financial literacy (Philippas & Avdoulas, 2020 ), financial inclusion (Hua & Huang, 2021 ; Kanga et al., 2021 ; Senyo, Osabutey, & Kan, 2021), the use of fintech as a research tool (Bradbury et al., 2019 ), and research on the concept of fintech itself (Bollaert et al., 2021 ). The authors used these four topics to successfully categorize all 216 articles in the research sample.

To guard against the threats to reliability (Neuendorf, 2017 ), we once again performed a pilot test on articles not included in the final data pool for this study. Following the adoption of the four research topics, this second pilot study was used as a training session for categorizing articles by research topic. Researchers independently categorized the articles in the pilot test based on the best fit among the four research topics. After all articles in the pilot test were categorized, the researchers compared their analyses. In instances where the independent categorizations did not match, the researchers re-evaluated the article collaboratively by reviewing the research category definitions, discussing the disagreement thoroughly, and collaboratively assigning the article to a single category. This process allowed the researchers to develop a collaborative interpretation of the research topic definitions (see Table 9 ). Once we established the topic definitions, we independently placed each article in one fintech category. As before, we categorized only a few articles at a time to minimize coder fatigue and thus protect intercoder reliability (Neuendorf, 2017 ).

Upon completion of the classification process, agreements and disagreements were tabulated. The percent agreement was 86.1% ( N = 216). Then, intercoder reliability ( κ = 0.860) using Cohen’s Kappa (Cohen, 1960 ) and Krippendorf’s Alpha (Krippendorff, 2013 ) for each methodology ( α = 0.815) was calculated. Neuendorf ( 2017 ) suggests that a Cohen’s kappa greater than 0.800 is considered acceptable. Krippendorff ( 2013 ) stated that researchers could use reliability scores greater than 0.800. Therefore, the calculations for intercoder reliability were well within the acceptable ranges. We calculated the reliability measures prior to discussing disagreements as mandated by Weber ( 1990 ). If the original reviewers did not agree on how a particular article was coded, a third reviewer arbitrated the discussion of how the disputed article was to be coded. This process resolved the disputes in all cases.

To identify gaps and needs in the research (Webster & Watson, 2002 ), we hope to paint a representative landscape of the current fintech literature base. To examine the current state of this research, the authors conducted a literature review and analysis in three phases. Phase 1 accumulated a representative pool of fintech articles, and the articles were then analyzed with respect to year of publication, journal, and author. Phase 2 briefly discussed the research strategies set forth by Scandura and Williams ( 2000 ) and the results of the classification of the articles by those research strategies. Phase 3 involved the creation and use of four fintech topics, a short discussion of each topic, and the results of the classification of each article within the research topics. These results are discussed in the following paragraphs.

Results of Phase 1

Using the described search criteria within the selected journals, we collected a total of 216 articles. For the complete list of Finance articles in our sample ( N = 146), see Appendix 1 . For the complete list of Information Systems articles in our sample ( N = 70), see Appendix 2 . In phase 1, we further analyzed the articles’ year of publication, journal, and author. Figure 3 shows the number of articles per year in our sample. Although no articles were collected prior to 2016, there is a dramatically increasing trend over the 6-year period of 2016 through 2021. From 2020 to 2021, the number of articles more than doubled, with N = 52 in 2020 and N = 105 in 2021. With fintech issues becoming ever more important to researchers and practitioners, this drastic increase comes as no surprise.

Number of fintech articles published per year

We analyzed the productivity of authors who published in this line of research by assigning scores based on each author’s share of each article. For projects with multiple authors, each co-author was given an equal share of the credit. An author who published an article alone was assigned a score of 1.0. For a two-author article, each author earned a score of 0.500, three authors shared 0.333, and so on. Authorship order was not calculated into this formula. We totaled the scores for each Finance author, then ranked the authors according to their totaled scores in descending order. The results of the top 43 fintech authors in Finance are displayed in Table 10 . This system rewards both quantity of research and ownership of research. The top ranked Finance researcher (Schwienbacher, A.) and the second ranked research (Selim, M.) both had a sole-author paper and co-authorship on another article in the Finance sample. All others who wrote a sole-author research article tied for third place. All of the remaining authors in this list co-authored more than one fintech research article published in Finance, so their scores are above 0.500.

Similarly, the scores for each Information Systems author were totaled, and the authors were sorted from highest to lowest scores. The results of the top 13 fintech authors in the Information Systems sample are displayed in Table 11 . This system rewards both quantity of research and ownership of research. The top ranked researcher (Gozman, D.) had co-authorship on many articles in the Information Systems sample. All the second-ranked authors had a sole author paper (score = 1.0). The remaining authors who had a score greater than 0.500 were also ranked in the sample. A score greater than 0.500 indicates having more than one co-authorship in the sample.

Results of Phase 2

The results of the categorization of the 216 articles according to the nine research strategies described by Scandura and Williams ( 2000 ) are summarized in Table 12 . Of the 216 articles, 104 articles (48.15%) were classified as Field Study—Secondary Data making this category the most used research strategy. With 62 articles (28.70%), Formal Theory/Literature Review was the second most prevalent research strategy. Following were Sample Survey with 23 articles (10.65%) and Field Study—Primary Data with 20 articles (9.26%). The remaining categories had three or fewer articles. These top four research strategies composed of 96.76% of the articles in the sample. No articles were classified as a Judgment Task nor a Field Experiment. These four strategies are exploratory in nature and indicate the beginnings of a body of research (Scandura & Williams, 2000 ). Further categorization and analysis of the articles with respect to fintech topic categories were conducted in the third phase of this research project.

Results of Phase 3

Table 13 shows the number of articles per fintech research topic category. These four categories provided a topic area classification for all the 216 articles in our research sample. Of the 216 articles, 38.43% were classified as “Research,” making it the most prevalent fintech topic category. This result is not surprising because the content analyzed was collected from research publishing outlets. Closely following were “Impact” and “Innovate” (21.76%) tying for second place. “Enhance” was the least popular with 18.06% of the articles. These four research strategies accounted for 100% of the articles in the sample. This illustration of the share of fintech research that is represented by each topic reveals the amount of attention fintech is receiving in Finance journals across a new, yet diverse, research stream.

Fintech research strategies versus topics

By plotting fintech research topics against research strategies (Table 14 ), many of the gaps in fintech research are exposed. In our minds, these gaps exist for two reasons. First, some of these research strategies are not prevalent in Finance and IS research. Because some top research journals do not accept papers that use non-traditional or qualitative research strategies, researchers tend to avoid unorthodox strategies. Second, some of these categories have not been studied because they represent a relatively new phenomenon, of which the research has not caught up with the business reality. The great news for researchers interested in fintech is that this domain should provide research opportunities for years to come.

Almost half (48.15%) of the journal articles in this study use the Field Study—Secondary Data research strategy across all research topics. Therefore, classifying the sources of the secondary data used in this research may be valuable for new researchers by providing them insights and sources for future research. The use of Formal Theory/Literature Review (28.7%) and Sample Survey (10.65%) research strategies indicates the exploratory nature of the current state of fintech research. We speculate four reasons for the top three strategies used to study fintech to be prevalent and appropriate for the early stages of research. First, secondary data is common in Finance research with the common practice of using freely available data from financial markets. This abundance of financial data is augmented by the availability of premium financial information services as a source of data for research projects. Second, in these exploratory years of fintech research, formal theory/literature reviews are appropriate to determine what other strategies are being used in the research and to find reference disciplines that are conducting related research. Third, researchers in business schools tend to be more skilled in administering literature reviews, field studies (with primary and secondary data), and sample surveys than in the strategies of laboratory experiment, field experiments, experimental simulation, judgment task, and computer simulation. Finally, organizations are less likely to commit to certain strategies (e.g., primary field studies and field experiments) because these strategies are more expensive for the organizations. These types of research strategies are very labor intensive to the organization being studied because they require records to be examined, personnel to be interviewed, and senior managers to devote large amounts of their expensive time to help facilitate the research project.

Contributions

To date, no study has examined fintech research topics in words, content, or methodologies. The purpose of this study is to synthesize the methodologies and content of all fintech article from the past 20 year encompassing all journals on the Australian Business Deans list that have a rating of A*, A, and B. This study finds that the majority of fintech research has been conducted over the past 4 years, with the number of articles significantly increasing during that period. The majority of this research is focused on banking, credit, lending, and intermediaries. However, many other subjects are yet to be covered in a robust manner. Despite the proliferation of fintech research, there unfortunately is no standard set of best practices or methodological norms that researchers can use as of yet. Our findings show that fintech research is in its infancy.

Limitations

The current analysis of the fintech literature in this study has limitations and should be enhanced with future research efforts. Future literature reviews could expand article searches to full article text searches, search a broader domain of research outlets (such as adding the C journals in the ABDC journal list), and include other fintech related search terms. Our literature analysis is meant to serve as a representative sample of articles and not a comprehensive and exhaustive analysis of the entire population of articles published on the topic of fintech.

This study provided a content analysis of the current state of the research with respect to research strategy and topic at the journals on the ABDC list. Other publication outlets may be publishing greater quantities of fintech research with similar quality as the journals in our sample.

Directions for future research

For researchers to continue to attempt to answer the important questions in fintech, future studies need to employ a wider variety of research strategies to investigate these important issues. Scandura and Williams ( 2000 ) stated that looking at research strategies employed over time by triangulation in each subject area can provide useful insights into how theories are developing. In addition to the lack of variety in research strategy, very little triangulation has occurred during the timeframe used to conduct this literature review. This absence of coordinated theory development causes the research in fintech to appear haphazard and unfocused. Clearly, future studies should consider the identified gaps and consider the future research role relative to generalizability, precision of measure, and realism of context.

Future efforts should also consider the four research topics with respect to the research strategies. To further investigate this body of research, future studies could explore the fintech topics in depth by creating subtopics within the four topics in the study. For example, fintech will be deployed by organizations to improve their current business processes for future study under the Enhance topic. For the Impact, many of these fintech modalities have not been in place long enough for researchers, practitioners, governments, and other stakeholders to collect analyze data on how industries, governments, and economies are affected on a short or long-time horizon. As previously unknown business models and technologies combine fintech and artificial intelligence, new opportunities for research will be presented for researchers and practitioners alike to explore Innovate topic. As the number and quality of research grows in Enhance, Impact, and Innovate grows, this will give researchers in disciplines as varied as Economics, Engineering, Psychology, Sociology, and others to contribute to the research body of fintech and how this concept is progressing across time and a variety of research streams.

Future studies could take a more in-depth look at the various business models or fintech strategies associated with this research stream. Moreover, much of the research in our sample reports the new technologies and issues in fintech without attempting to explain the fundamental issues of the technology implemented or the effects of these technologies on individuals, organizations, and society. This is to be expected in the exploratory stages of research in a subject area.

This study used the content analysis methodology to create a current, cross-disciplinary image of the current state of fintech research in the top Finance and Information Systems journals across time, research strategy, and topic to classify this concept of financial technologies. Further, this study illustrates the future potential of fintech domain across both research strategy and topic. Despite the efforts of the researchers in the article sample, fintech is in the beginning stages of the research stream. The bad news is that much research needs to take place in this domain using a variety of research strategies over time to develop best practices for practitioners and theory for the research domain. In this sample, most of the research had been published in the previous four years, and the good news for researchers and practitioners alike is that many of the topics and research strategies in this research are open for future research efforts including some research strategy and topic areas that are completely unresearched (Table 14 ). As more practitioners deploy more fintech modalities, researchers will have the opportunity to create even more novel and rigorous research studies. We hope that this content analysis has laid the foundation for such efforts that will enhance the body of knowledge and theoretical progression relative to fintech.

ABDC. (2019). ABDC journal quality list. Retrieved from https://abdc.edu.au/research/abdc-journal-quality-list/

Adams, J., Hayunga, D., Mansi, S., Reeb, D., & Verardi, V. (2019). Identifying and treating outliers in finance. Financial Management, 48 (2), 345–384. https://doi.org/10.1111/fima.12269

Article Google Scholar

Alt, R., Beck, R., & Smits, M. T. (2018). Fintech and the transformation of the financial industry. Electronic Markets, 28 (3), 235–243. https://doi.org/10.1007/s12525-018-0310-9

Benedetti, H., & Nikbakht, E. (2021). Returns and network growth of digital tokens after cross-listings. Journal of Corporate Finance, 66 . https://doi.org/10.1016/j.jcorpfin.2020.101853

Benoit, S., Hurlin, C., & Perignon, C. (2019). Pitfalls in systemic-risk scoring. Journal of Financial Intermediation, 38 , 19–44. https://doi.org/10.1016/j.jfi.2018.05.004

Bertsch, C., Hull, I., Qi, Y. J., & Zhang, X. (2020). Bank misconduct and online lending. Journal of Banking & Finance, 116 . https://doi.org/10.1016/j.jbankfin.2020.105822.

Bollaert, H., Lopez-de-Silanes, F., & Schwienbacher, A. (2021). Fintech and access to finance. Journal of Corporate Finance, 68 . https://doi.org/10.1016/j.jcorpfin.2021.101941.

Boyd, J. H., & De Nicolo, G. (2005). The theory of bank risk taking and competition revisited. Journal of Finance, 60 (3), 1329–1343. https://doi.org/10.1111/j.1540-6261.2005.00763.x

Bradbury, M. A. S., Hens, T., & Zeisberger, S. (2019). How persistent are the effects of experience sampling on investor behavior? Journal of Banking & Finance, 98 , 61–79. https://doi.org/10.1016/j.jbankfin.2018.10.014

Briner, R. B., Denyer, D., & Rousseau, D. M. (2009). Evidence-based management: Concept cleanup time? Academy of Management Perspectives, 23 (4), 19–32. https://doi.org/10.5465/amp.2009.45590138

Campbell, D. T., & Cook, T. D. (1976). The design and conduct of quasi-experiments and true experiments in field settings. In M. D. Dunnette (Ed.), Handbook of industrial and organizational psychology . Chicago, IL: Rand McNally.

Christensen, C. M. A. (2016). The innovator’s dilemma: When new technologies cause great firms to fail / Clayton M. Christensen . Boston: Harvard Business Review Press.

Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20 (1), 37–46. https://doi.org/10.1177/001316446002000104

Corley, J. K., Jourdan, Z., & Ingram, W. R. (2013). Internet marketing: A content analysis of the research. Electronic Markets, 23 (3), 177–204. https://doi.org/10.1007/s12525-012-0118-y

Cumbie, B., Jourdan, Z., Peachey, T., Dugo, T., & Craighead, C. (2005). Enterprise resource planning research: Where are we now and where should we go from here? Journal of Information Technology Theory and Application (JITTA), 7 (2), 21–36.

Google Scholar

Di Maggio, M., & Yao, V. (2021). Fintech borrowers: Lax screening or cream-skimming? Review of Financial Studies, 34 (10), 4565–4618. https://doi.org/10.1093/rfs/hhaa142

Farooq, U., & Jibran, A. Q. (2018). Scope, measurement, impact size and determinants of indirect cost of financial distress: A systematic literature review. Qualitative Research in Financial Markets, 10 (1), 111–129. https://doi.org/10.1108/qrfm-08-2017-0080

Fung, D. W. H., Lee, W. Y., Yeh, J. J. H., & Yuen, F. L. (2020). Friend or foe: The divergent effects of fintech on financial stability. Emerging Markets Review, 45 . https://doi.org/10.1016/j.ememar.2020.100727.

Fuster, A., Plosser, M., Schnabl, P., & Vickery, J. (2019). The role of technology in mortgage lending. Review of Financial Studies, 32 (5), 1854–1899. https://doi.org/10.1093/rfs/hhz018

Gerrans, P., Baur, D. G., & Lavagna-Slater, S. (2021). Fintech and responsibility: Buy-now-pay-later arrangements. Australian Journal of Management . https://doi.org/10.1177/03128962211032448

Goetz, M. R. (2018). Competition and bank stability. Journal of Financial Intermediation, 35 , 57–69. https://doi.org/10.1016/j.jfi.2017.06.001

Hornuf, L., Klus, M. F., Lohwasser, T. S., & Schwienbacher, A. (2021). How do banks interact with fintech startups? Small Business Economics, 57 (3), 1505–1526. https://doi.org/10.1007/s11187-020-00359-3

Hua, X. P., & Huang, Y. P. (2021). Understanding China’s fintech sector: Development, impacts and risks. European Journal of Finance, 27 (4–5), 321–333. https://doi.org/10.1080/1351847x.2020.1811131

Jagtiani, J., & Lemieux, C. (2019). The roles of alternative data and machine learning in fintech lending: Evidence from the LendingClub consumer platform. Financial Management, 48 (4), 1009–1029. https://doi.org/10.1111/fima.12295

Jiang, J. L., Liao, L., Wang, Z. W., & Zhang, X. Y. (2021). Government affiliation and peer-to-peer lending platforms in China. Journal of Empirical Finance, 62 , 87–106. https://doi.org/10.1016/j.jempfin.2021.02.004

Jourdan, Z., Rainer, R. K., & Marshall, T. E. (2008). Business intelligence: An analysis of the literature. Information Systems Management, 25 (2), 121–131. https://doi.org/10.1080/10580530801941512

Kanga, D., Oughton, C., Harris, L., & Murinde, V. (2021). The diffusion of fintech, financial inclusion and income per capita. European Journal of Finance . https://doi.org/10.1080/1351847x.2021.1945646

Kim, J. H., & Ji, P. I. (2015). Significance testing in empirical finance: A critical review and assessment. Journal of Empirical Finance, 34 , 1–14. https://doi.org/10.1016/j.jempfin.2015.08.006

Kim, W. C., Kwon, D. G., Lee, Y., Kim, J. H., & Lin, C. (2020). Personalized goal-based investing via multi-stage stochastic goal programming. Quantitative Finance, 20 (3), 515–526. https://doi.org/10.1080/14697688.2019.1662079

Krippendorff, K. (2013). Content analysis: An introduction to its methodology / Klaus Krippendorff . Los Angeles [etc.]: SAGE Publications.

Lagna, A., & Ravishankar, M. N. (2022). Making the world a better place with fintech research. Information Systems Journal, 32 (1), 61–102. https://doi.org/10.1111/isj.12333

Li, Y. Q., Spigt, R., & Swinkels, L. (2017). The impact of fintech start-ups on incumbent retail banks’ share prices. Financial Innovation, 3 (1). https://doi.org/10.1186/s40854-017-0076-7.

Lin, T. C., & Pursiainen, V. (2021). The round number heuristic and entrepreneur crowdfunding performance. Journal of Corporate Finance, 68 . https://doi.org/10.1016/j.jcorpfin.2021.101894.

McGrath, J. E. (1982). Dilemmatics: The study of research choices and delimmas . Sage Publications.

Neuendorf, K. A. (2002). The content analysis guidebook (1st ed.). Thousand Oaks, Calif. [etc.]: Sage Publications.

Neuendorf, K. A. (2017). The content analysis guidebook (2nd ed.). Thousand Oaks, California: SAGE Publications, Inc.

Philippas, N. D., & Avdoulas, C. (2020). Financial literacy and financial well-being among generation-Z university students: Evidence from Greece. European Journal of Finance, 26 (4–5), 360–381. https://doi.org/10.1080/1351847x.2019.1701512

Philippon, T. (2015). Has the US finance industry become less efficient? On the theory and measurement of financial intermediation. American Economic Review, 105 (4), 1408–1438. https://doi.org/10.1257/aer.20120578

Scandura, T. A., & Williams, E. A. (2000). Research methodology in management: Current practices, trends, and implications for future research. Academy of Management Journal, 43 (6), 1248–1264. https://doi.org/10.2307/1556348

Schueffel, P. (2016). Taming the beast: A scientific definition of fintech. SSRN Electronic Journal ; ISSN 1556–5068 . https://doi.org/10.2139/ssrn.3097312.

Stoeckli, E., Dremel, C., & Uebernickel, F. (2018). Exploring characteristics and transformational capabilities of InsurTech innovations to understand insurance value creation in a digital world. Electronic Markets, 28 (3), 287–305. https://doi.org/10.1007/s12525-018-0304-7

Thakor, A. V. (1999). Information technology and financial services consolidation. Journal of Banking & Finance, 23 (2–4), 697–700. https://doi.org/10.1016/s0378-4266(98)00104-6

Thakor, A. V. (2020). Fintech and banking: What do we know? Journal of Financial Intermediation, 41 . https://doi.org/10.1016/j.jfi.2019.100833

Weber, R. P. (1990). Basic content analysis (2nd ed.). Nowbury Park: Sage Publications.

Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. MIS Quarterly, 26 (2), XIII-XXIII. Retrieved from https://www.jstor.org/stable/4132319

Zhao, X. J., Hou, W. X., An, J. F., Liu, X. D., & Zhang, Y. (2021). Initial coin offerings: What rights do investors have? European Journal of Finance, 27 (4–5), 305–320. https://doi.org/10.1080/1351847x.2020.1858130

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Appendix 1 Sample of 146 fintech finance articles

Agarwal, S., & Zhang, J. (2020). Fintech, lending and payment innovation: A review. Asia-Pacific Journal of Financial Studies, 49 (3), 353-367. https://doi.org/10.1111/ajfs.12294

Ahmed, S., Grobys, K., & Sapkota, N. (2020). Profitability of technical trading rules among cryptocurrencies with privacy function. Finance Research Letters, 35 . https://doi.org/10.1016/j.frl.2020.101495

Akyildirim, E., Corbet, S., Sensoy, A., & Yarovaya, L. (2020). The impact of blockchain related name changes on corporate performance. Journal of Corporate Finance, 65 . https://doi.org/10.1016/j.jcorpfin.2020.101759

Akyildirim, E., Sensoy, A., Gulay, G., Corbet, S., & Salari, H. N. (2021). Big data analytics, order imbalance and the predictability of stock returns. Journal of Multinational Financial Management, 62 . https://doi.org/10.1016/j.mulfin.2021.100717

Albarrak, M. S., & Alokley, S. A. (2021). Fintech: Ecosystem, opportunities and challenges in Saudi Arabia. Journal of Risk and Financial Management, 14 (10). https://doi.org/10.3390/jrfm14100460

Altamura, C. E., & Daunton, M. (2020). Finance, financiers and financial centres: a special issue in honour of Youssef Cassis Introduction. Financial History Review, 27 (3), 283-302. https://doi.org/10.1017/s0968565020000153

Altwijry, O. I., Mohammed, M. O., Hassan, M. K., & Selim, M. Developing a Shari'ah based fintech money creation free SFMCF model for Islamic banking. International Journal of Islamic and Middle Eastern Finance and Management . https://doi.org/10.1108/imefm-05-2021-0189

Arner, D. W., Barberis, J., & Buckley, R. P. (2016). 150 YEARS OF FINTECH: An evolutionary analysis. Jassa-the Finsia Journal of Applied Finance (3), 22-29. Retrieved from https://search.informit.org/doi/10.3316/ielapa.419780653701585

Ascarya, A. (2021). The role of Islamic social finance during Covid-19 pandemic in Indonesia's economic recovery. International Journal of Islamic and Middle Eastern Finance and Management . https://doi.org/10.1108/imefm-07-2020-0351

Azarenkova, G., Shkodina, I., Samorodov, B., Babenko, M., & Onishchenko, I. (2018). The influence of financial technologies on the global financial system stability. Investment Management and Financial Innovations, 15 (4), 229-238. https://doi.org/10.21511/imfi.15(4).2018.19

Ba, S. S., Wei, W., & Yuan, H. M. (2021). How does active change affect investment efficiency? Evidence from monthly account-level data on Chinese online platform. Emerging Markets Finance and Trade . https://doi.org/10.1080/1540496x.2021.1965984

Baber, H. (2020). Financial inclusion and fintech: A comparative study of countries following Islamic finance and conventional finance. Qualitative Research in Financial Markets, 12 (1), 24-42. https://doi.org/10.1108/qrfm-12-2018-0131

Baek, H. Y., Cho, D. D., Jordan, R. A., & Kuvvet, E. (2021). The differential effect of social disclosure on loan funding and loan repayment: evidence from fixed-rate peer-to-peer lending. Managerial Finance, 47 (3), 394-412. https://doi.org/10.1108/mf-02-2020-0079

Banna, H., Hassan, M. K., Ahmad, R., & Alam, M. R. (2021). Islamic banking stability amidst the COVID-19 pandemic: The role of digital financial inclusion. International Journal of Islamic and Middle Eastern Finance and Management . https://doi.org/10.1108/imefm-08-2020-0389

Banna, H., Hassan, M. K., & Rashid, M. (2021). Fintech-based financial inclusion and bank risk-taking: Evidence from OIC countries. Journal of International Financial Markets Institutions & Money, 75 . https://doi.org/10.1016/j.intfin.2021.101447

Bao, Z. Y., & Huang, D. F. (2021). Shadow banking in a crisis: Evidence from fintech during COVID-19. Journal of Financial and Quantitative Analysis, 56 (7), 2320-2355. https://doi.org/10.1017/s0022109021000430

Bertsch, C., Hull, I., Qi, Y. J., & Zhang, X. (2020). Bank misconduct and online lending. Journal of Banking & Finance, 116 . https://doi.org/10.1016/j.jbankfin.2020.105822

Bhatia, A., Chandani, A., Atiq, R., Mehta, M., & Divekar, R. (2021). Artificial intelligence in financial services: A qualitative research to discover robo-advisory services. Qualitative Research in Financial Markets, 13 (5), 632-654. https://doi.org/10.1108/qrfm-10-2020-0199

Bhatia, A., Chandani, A., & Chhateja, J. (2020). Robo advisory and its potential in addressing the behavioral biases of investors - A qualitative study in Indian context. Journal of Behavioral and Experimental Finance, 25 . https://doi.org/10.1016/j.jbef.2020.100281

Blach, J., & Klimontowicz, M. (2021). The Determinants of PayTech's success in the mobile payment market-The case of BLIK. Journal of Risk and Financial Management, 14 (9). https://doi.org/10.3390/jrfm14090422

Bollaert, H., Lopez-de-Silanes, F., & Schwienbacher, A. (2021). Fintech and access to finance. Journal of Corporate Finance, 68 . https://doi.org/10.1016/j.jcorpfin.2021.101941

Bradbury, M. A. S., Hens, T., & Zeisberger, S. (2019). How persistent are the effects of experience sampling on investor behavior? Journal of Banking & Finance, 98 , 61-79. https://doi.org/10.1016/j.jbankfin.2018.10.014

Brammertz, W., & Mendelowitz, A. I. (2018). From digital currencies to digital finance: The case for a smart financial contract standard. Journal of Risk Finance, 19 (1), 76-92. https://doi.org/10.1108/jrf-02-2017-0025

Brenner, L., & Meyll, T. (2020). Robo-advisors: A substitute for human financial advice? Journal of Behavioral and Experimental Finance, 25 . https://doi.org/10.1016/j.jbef.2020.100275

Buchak, G., Matvos, G., Piskorski, T., & Seru, A. (2018). Fintech, regulatory arbitrage, and the rise of shadow banks. Journal of Financial Economics, 130 (3), 453-483. https://doi.org/10.1016/j.jfineco.2018.03.011

Caglayan, M., Talavera, O., Xiong, L., & Zhang, J. (2020). What does not kill us makes us stronger: The story of repetitive consumer loan applications. European Journal of Finance . https://doi.org/10.1080/1351847x.2020.1793792

Caglayan, M., Talavera, O., & Zhang, W. (2021). Herding behaviour in P2P lending markets. Journal of Empirical Finance, 63 , 27-41. https://doi.org/10.1016/j.jempfin.2021.05.005

Chava, S., Ganduri, R., Paradkar, N., & Zhang, Y. F. (2021). Impact of marketplace lending on consumers' future borrowing capacities and borrowing outcomes. Journal of Financial Economics, 142 (3), 1186-1208. https://doi.org/10.1016/j.jfineco.2021.06.005

Chen, M. A., Wu, Q. X., & Yang, B. Z. (2019). How valuable is fintech innovation? Review of Financial Studies, 32 (5), 2062-2106. https://doi.org/10.1093/rfs/hhy130

Chen, X. E., & Wang, C. (2021). Information disclosure in China's rising securitization market. International Journal of Financial Studies, 9 (4). https://doi.org/10.3390/ijfs9040066

Cheng, M. Y., & Qu, Y. (2020). Does bank fintech reduce credit risk? Evidence from China. Pacific-Basin Finance Journal, 63 . https://doi.org/10.1016/j.pacfin.2020.101398

Chong, F. H. L. (2021). Enhancing trust through digital Islamic finance and blockchain technology. Qualitative Research in Financial Markets, 13 (3), 328-341. https://doi.org/10.1108/qrfm-05-2020-0076

Chuen, D. L. K. (2018). Fintech and alternativeiInvestment. Journal of Alternative Investments, 20 (3), 6-15. https://doi.org/10.3905/jai.2018.20.3.006

Cumming, D. J., Johan, S., & Pant, A. (2019). Regulation of the crypto-economy: Managing risks, challenges, and regulatory uncertainty. Journal of Risk and Financial Management, 12 (3). https://doi.org/10.3390/jrfm12030126

Daluwathumullagamage, D. J., & Sims, A. (2021). Fantastic Beasts: Blockchain based banking. Journal of Risk and Financial Management, 14 (4). https://doi.org/10.3390/jrfm14040170

Danbolt, J., Eshraghi, A., & Lukas, M. (2021). Investment transparency and the disposition effect. European Financial Management . https://doi.org/10.1111/eufm.12329

Daragmeh, A., Lentner, C., & Sagi, J. (2021). Fintech payments in the era of COVID-19: Factors influencing behavioral intentions of "Generation X"in Hungary to use mobile payment. Journal of Behavioral and Experimental Finance, 32 . https://doi.org/10.1016/j.jbef.2021.100574

Das, S. R. (2019). The future of fintech. Financial Management, 48 (4), 981-1007. https://doi.org/10.1111/fima.12297

Demir, A., Pesque-Cela, V., Altunbas, Y., & Murinde, V. (2020). Fintech, financial inclusion and income inequality: a quantile regression approach. European Journal of Finance . https://doi.org/10.1080/1351847x.2020.1772335

Deng, L. R., Lv, Y. B., Liu, Y., & Zhao, Y. W. (2021). Impact of fintech on bank risk-taking: Evidence from China. Risks, 9 (5). https://doi.org/10.3390/risks9050099

Di Maggio, M., & Yao, V. (2021). Fintech borrowers: Lax screening or cream-skimming? Review of Financial Studies, 34 (10), 4565-4618. https://doi.org/10.1093/rfs/hhaa142

Dranev, Y., Frolova, K., & Ochirova, E. (2019). The impact of fintech M&A on stock returns. Research in International Business and Finance, 48 , 353-364. https://doi.org/10.1016/j.ribaf.2019.01.012

Dugast, J., & Foucault, T. (2018). Data abundance and asset price informativeness. Journal of Financial Economics, 130 (2), 367-391. https://doi.org/10.1016/j.jfineco.2018.07.004

Elsaid, H. M. A review of literature directions regarding the impact of fintech firms on the banking industry. Qualitative Research in Financial Markets . https://doi.org/10.1108/qrfm-10-2020-0197

Fahlenbrach, R., & Frattaroli, M. (2021). ICO investors. Financial Markets and Portfolio Management, 35 (1), 1-59. https://doi.org/10.1007/s11408-020-00366-0

Faloon, M., & Scherer, B. (2017). Individualization of robo-advice. Journal of Wealth Management, 20 (1), 30-36. https://doi.org/10.3905/jwm.2017.20.1.030

Fang, H., Chung, C. P., Lu, Y. C., Lee, Y. H., & Wang, W. H. (2021). The impacts of investors' sentiments on stock returns using fintech approaches. International Review of Financial Analysis, 77 . https://doi.org/10.1016/j.irfa.2021.101858

Farag, H., & Johan, S. (2021). How alternative finance informs central themes in corporate finance. Journal of Corporate Finance, 67 . https://doi.org/10.1016/j.jcorpfin.2020.101879

Foglia, M., Recchioni, M. C., & Polinesi, G. (2021). Smart beta allocation and macroeconomic variables: The impact of COVID-19. Risks, 9 (2). https://doi.org/10.3390/risks9020034

Fuster, A., Plosser, M., Schnabl, P., & Vickery, J. (2019). The role of technology in mortgage lending. Review of Financial Studies, 32 (5), 1854-1899. https://doi.org/10.1093/rfs/hhz018

Gachter, I., & Gachter, M. (2021). Success factors in ICOs: Individual firm characteristics or lucky timing? Finance Research Letters, 40 . https://doi.org/10.1016/j.frl.2020.101715

Glavina, S., Aidrus, I., & Trusova, A. (2021). Assessment of the competitiveness of Islamic fintech implementation: A composite indicator for cross-country analysis. Journal of Risk and Financial Management, 14 (12). https://doi.org/10.3390/jrfm14120602

Goldstein, I., Jiang, W., & Karolyi, G. A. (2019). To fintech and beyond. Review of Financial Studies, 32 (5), 1647-1661. https://doi.org/10.1093/rfs/hhz025

Golub, A., Grossmass, L., & Poon, S. H. (2021). Ultra-short tenor yield curve for intraday trading and settlement. European Journal of Finance, 27 (4-5), 441-459. https://doi.org/10.1080/1351847x.2019.1662821

Gong, Q., Liu, C., Peng, Q. N., & Wang, L. Y. (2020). Will CEOs with banking experience lower default risks? Evidence from P2P lending platforms in China. Finance Research Letters, 36 . https://doi.org/10.1016/j.frl.2020.101461

Gonzalez, L. (2020). Blockchain, herding and trust in peer-to-peer lending. Managerial Finance, 46 (6), 815-831. https://doi.org/10.1108/mf-09-2018-0423

Grabowski, M. (2021). Legal aspects of "White-Label" banking in the European, Polish and German law. Journal of Risk and Financial Management, 14 (6). https://doi.org/10.3390/jrfm14060280

Grobys, K., Ahmed, S., & Sapkota, N. (2020). Technical trading rules in the cryptocurrency market. Finance Research Letters, 32 . https://doi.org/10.1016/j.frl.2019.101396

Gupta, M., Verma, S., & Pachare, S. (2021). An analysis of conventional and alternative financing-customers' perspective. International Journal of Finance & Economics . https://doi.org/10.1002/ijfe.2541

Han, J. J., & Kim, H. J. (2021). Stock price prediction using multiple valuation methods based on artificial neural networks for KOSDAQ IPO companies. Investment Analysts Journal, 50 (1), 17-31. https://doi.org/10.1080/10293523.2020.1870860

Harasim, J. (2021). Fintechs, Bigtechs and banks-When cooperation and when competition? Journal of Risk and Financial Management, 14 (12). https://doi.org/10.3390/jrfm14120614

Ho, M.-T., Le, N.-T. B., Tran, H.-L. D., Nguyen, Q.-H., Pham, M.-H., Ly, M. H., Ho, M.-T., Nguyen, M.-H. & Vuong, Q.-H. (2021). A systematic and critical review on the research landscape of finance in Vietnam from 2008 to 2020. Journal of Risk and Financial Management, 14 (5). https://doi.org/10.3390/jrfm14050219

Hua, X. P., & Huang, Y. P. (2021). Understanding China's fintech sector: development, impacts and risks. European Journal of Finance, 27 (4-5), 321-333. https://doi.org/10.1080/1351847x.2020.1811131

Hudaefi, F. A. (2020). How does Islamic fintech promote the SDGs? Qualitative evidence from Indonesia. Qualitative Research in Financial Markets, 12 (4), 353-366. https://doi.org/10.1108/qrfm-05-2019-0058

Huibers, F. (2021). Regulatory response to the rise of fintech credit in The Netherlands. Journal of Risk and Financial Management, 14 (8). https://doi.org/10.3390/jrfm14080368

Iman, N. (2018). Assessing the dynamics of fintech in Indonesia. Investment Management and Financial Innovations, 15 (4), 296-303. https://doi.org/10.21511/imfi.15(4).2018.24

Imerman, M. B., & Fabozzi, F. J. (2020). Cashing in on innovation: A taxonomy of fintech. Journal of Asset Management, 21 (3), 167-177. https://doi.org/10.1057/s41260-020-00163-4

Ishak, M. S. I., & Rahman, M. H. (2021). Equity-based Islamic crowdfunding in Malaysia: A potential application for mudharabah. Qualitative Research in Financial Markets, 13 (2), 183-198. https://doi.org/10.1108/qrfm-03-2020-0024

Jiang, J. L., Liao, L., Lu, X., Wang, Z. W., & Xiang, H. Y. (2021). Deciphering big data in consumer credit evaluation. Journal of Empirical Finance, 62 , 28-45. https://doi.org/10.1016/j.jempfin.2021.01.009

Jiang, J. L., Liao, L., Wang, Z. W., & Zhang, X. Y. (2021). Government affiliation and peer-to-peer lending platforms in China. Journal of Empirical Finance, 62 , 87-106. https://doi.org/10.1016/j.jempfin.2021.02.004

Jun, J., & Yeo, E. (2016). Entry of fintech firms and competition in the retail payments market. Asia-Pacific Journal of Financial Studies, 45 (2), 159-184. https://doi.org/10.1111/ajfs.12126

Junger, M., & Mietzner, M. (2020). Banking goes digital: The adoption of fintech services by German households. Finance Research Letters, 34 . https://doi.org/10.1016/j.frl.2019.08.008

Kavassalis, P., Stieber, H., Breymann, W., Saxton, K., & Gross, F. J. (2018). An innovative RegTech approach to financial risk monitoring and supervisory reporting. Journal of Risk Finance, 19 (1), 39-55. https://doi.org/10.1108/jrf-07-2017-0111

Kim, W. C., Kwon, D. G., Lee, Y., Kim, J. H., & Lin, C. (2020). Personalized goal-based investing via multi-stage stochastic goal programming. Quantitative Finance, 20 (3), 515-526. https://doi.org/10.1080/14697688.2019.1662079

Kliber, A., Bedowska-Sojka, B., Rutkowska, A., & Swierczynska, K. (2021). Triggers and obstacles to the development of the fintech sector in Poland. Risks, 9 (2). https://doi.org/10.3390/risks9020030

Knewtson, H. S., & Rosenbaum, Z. A. (2020). Toward understanding fintech and its industry. Managerial Finance, 46 (8), 1043-1060. https://doi.org/10.1108/mf-01-2020-0024

Koziuk, V. (2021). Confidence in digital money: Are central banks more trusted than age is matter? Investment Management and Financial Innovations, 18 (1), 12-32. https://doi.org/10.21511/imfi.18(1).2021.02

Lanfranchi, D., & Grassi, L. (2022). Examining insurance companies' use of technology for innovation. Geneva Papers on Risk and Insurance-Issues and Practice . https://doi.org/10.1057/s41288-021-00258-y

Le, L. T., Yarovaya, L., & Nasir, M. A. (2021). Did COVID-19 change spillover patterns between fintech and other asset classes? Research in International Business and Finance, 58 . https://doi.org/10.1016/j.ribaf.2021.101441

Le, T. D. Q., Ho, T. H., Nguyen, D. T., & Ngo, T. (2021). Fintech credit and bank efficiency: International evidence. International Journal of Financial Studies, 9 (3). https://doi.org/10.3390/ijfs9030044

Lee, A. D., Li, M. L., & Zheng, H. H. (2020). Bitcoin: Speculative asset or innovative technology? Journal of International Financial Markets Institutions & Money, 67 . https://doi.org/10.1016/j.intfin.2020.101209

Lee, C. C. A., Li, X. R., Yu, C. H., & Zhao, J. S. (2021). Does fintech innovation improve bank efficiency? Evidence from China's banking industry. International Review of Economics & Finance, 74 , 468-483. https://doi.org/10.1016/j.iref.2021.03.009

Leinweber, D. (2017). Fintech codgers look back 25 years. Journal of Investing, 26 (1), 33-45. https://doi.org/10.3905/joi.2017.26.1.033

Li, J. P., Li, J. Y., Zhu, X. Q., Yao, Y. H., & Casu, B. (2020). Risk spillovers between fintech and traditional financial institutions: Evidence from the U.S. International Review of Financial Analysis, 71 . https://doi.org/10.1016/j.irfa.2020.101544

Li, W. P., & Mei, F. (2020). Asset returns in deep learning methods: An empirical analysis on SSE 50 and CSI 300. Research in International Business and Finance, 54 . https://doi.org/10.1016/j.ribaf.2020.101291

Lin, T. C., & Pursiainen, V. (2021). The round number heuristic and entrepreneur crowdfunding performance. Journal of Corporate Finance, 68 . https://doi.org/10.1016/j.jcorpfin.2021.101894

Ling, S. X., Pei, T. Y., Li, Z. H., & Zhang, Z. P. (2021). Impact of COVID-19 on financial constraints and the moderating effect of financial technology. Emerging Markets Finance and Trade, 57 (6), 1675-1688. https://doi.org/10.1080/1540496x.2021.1904883

Liu, M., Wu, W. F., & Yu, T. (2019). Information, incentives, and effects of risk-sharing on the real economy. Pacific-Basin Finance Journal, 57 . https://doi.org/10.1016/j.pacfin.2018.12.004

Loo, M. K. L. (2019). Enhancing financial inclusion in ASEAN: Identifying the best growth markets for fintech. Journal of Risk and Financial Management, 12 (4). https://doi.org/10.3390/jrfm12040181

Luo, D., Mishra, T., Yarovaya, L., & Zhang, Z. (2021). Investing during a fintech revolution: Ambiguity and return risk in cryptocurrencies. Journal of International Financial Markets Institutions & Money, 73 . https://doi.org/10.1016/j.intfin.2021.101362

Maskara, P. K., Kuvvet, E., & Chen, G. X. (2021). The role of P2P platforms in enhancing financial inclusion in the United States: An analysis of peer-to-peer lending across the rural-urban divide. Financial Management, 50 (3), 747-774. https://doi.org/10.1111/fima.12341

McKillop, D., French, D., Quinn, B., Sobiech, A. L., & Wilson, J. O. S. (2020). Cooperative financial institutions: A review of the literature. International Review of Financial Analysis, 71 . https://doi.org/10.1016/j.irfa.2020.101520

Mhlanga, D. (2020). Industry 4.0 in Finance: The impact of artificial intelligence (AI) on digital financial inclusion. International Journal of Financial Studies, 8 (3). https://doi.org/10.3390/ijfs8030045

Miglo, A. (2021). STO vs. ICO: A theory of token issues under moral hazard and demand uncertainty. Journal of Risk and Financial Management, 14 (6). https://doi.org/10.3390/jrfm14060232

Mishchenko, S., Naumenkova, S., Mishchenko, V., & Dorofeiev, D. (2021). Innovation risk management in financial institutions. Investment Management and Financial Innovations, 18 (1), 191-203. https://doi.org/10.21511/imfi.18(1).2021.16

Najaf, K., Schinckus, C., & Yoong, L. C. (2021). VaR and market value of fintech companies: an analysis and evidence from global data. Managerial Finance, 47 (7), 915-936. https://doi.org/10.1108/mf-04-2020-0169

Nastiti, N. D., & Kasri, R. A. (2019). The role of banking regulation in the development of Islamic banking financing in Indonesia. International Journal of Islamic and Middle Eastern Finance and Management, 12 (5), 643-662. https://doi.org/10.1108/imefm-10-2018-0365

Neale, F. R., Drake, P. P., & Konstantopoulos, T. (2020). InsurTech and the disruption of the insurance industry. Journal of Insurance Issues, 43 (2), 64-96. Retrieved from https://www.jstor.org/stable/26931211

Olsen, R., Battiston, S., Caldarelli, G., Golub, A., Nikulin, M., & Ivliev, S. (2018). Case study of Lykke exchange: Architecture and outlook. Journal of Risk Finance, 19 (1), 26-38. https://doi.org/10.1108/jrf-12-2016-0168

Ozik, G., Sadka, R., & Shen, S. Y. (2021). Flattening the illiquidity curve: Retail trading during the COVID-19 lockdown. Journal of Financial and Quantitative Analysis, 56 (7), 2356-2388. https://doi.org/10.1017/s0022109021000387

Ozili, P. K. (2022). Banking sector earnings management using loan loss provisions in the fintech era. International Journal of Managerial Finance, 18 (1), 75-93. https://doi.org/10.1108/ijmf-07-2020-0369

Petrushenko, Y., Kozarezenko, L., Glinska-Newes, A., Tokarenko, M., & But, M. (2018). The opportunities of engaging fintech companies into the system of crossborder money transfers in Ukraine. Investment Management and Financial Innovations, 15 (4), 332-344. https://doi.org/10.21511/imfi.15(4).2018.27

Petukhina, A. A., Reule, R. C. G., & Hardle, W. K. (2021). Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies. European Journal of Finance, 27 (1-2), 8-30. https://doi.org/10.1080/1351847x.2020.1789684

Phan, D. H. B., Narayan, P. K., Rahman, R. E., & Hutabarat, A. R. (2020). Do financial technology firms influence bank performance? Pacific-Basin Finance Journal, 62 . https://doi.org/10.1016/j.pacfin.2019.101210

Philippas, N. D., & Avdoulas, C. (2020). Financial literacy and financial well-being among generation-Z university students: Evidence from Greece. European Journal of Finance, 26 (4-5), 360-381. https://doi.org/10.1080/1351847x.2019.1701512

Pu, R. H., Teresiene, D., Pieczulis, I., Kong, J., & Yue, X. G. (2021). The interaction between banking sector and financial technology companies: Qualitative assessment-A case of Lithuania. Risks, 9 (1). https://doi.org/10.3390/risks9010021

Putri, W. H., Nurwiyanta, N., Sungkono, S., & Wahyuningsih, T. (2019). The emerging fintech and financial slack on corporate financial performance. Investment Management and Financial Innovations, 16 (2), 348-354. https://doi.org/10.21511/imfi.16(2).2019.29

Rosavina, M., Rahadi, R. A., Kitri, M. L., Nuraeni, S., & Mayangsari, L. (2019). P2P lending adoption by SMEs in Indonesia. Qualitative Research in Financial Markets, 11 (2), 260-279. https://doi.org/10.1108/qrfm-09-2018-0103

Rupeika-Apoga, R., & Wendt, S. (2021). Fintech in Latvia: Status quo, current developments, and challenges ahead. Risks, 9 (10). https://doi.org/10.3390/risks9100181

Santosa, P. W. (2020). Determinants of price reversal in high-frequency trading: Empirical evidence from Indonesia. Investment Management and Financial Innovations, 17 (1), 175-187. https://doi.org/10.21511/imfi.17(1).2020.16

Savchuk, N., Bludova, T., Leonov, D., Murashko, O., & Shelud'Ko, N. (2021). Innovation imperatives of global financial innovation and development of their matrix models. Investment Management and Financial Innovations, 18 (3), 312-326. https://doi.org/10.21511/imfi.18(3).2021.26

Schulte, P., & Liu, G. (2018). Fintech is merging with IoT and AI to challenge banks: How entrenched interests can prepare. Journal of Alternative Investments, 20 (3), 41-57. https://doi.org/10.3905/jai.2018.20.3.041

Schwienbacher, A. (2019). Equity crowdfunding: Anything to celebrate? Venture Capital, 21 (1), 65-74. https://doi.org/10.1080/13691066.2018.1559010

Seiler, V., & Fanenbruck, K. M. (2021). Acceptance of digital investment solutions: The case of robo advisory in Germany. Research in International Business and Finance, 58 . https://doi.org/10.1016/j.ribaf.2021.101490

Selim, M. (2021). The effects of eliminating Riba in foreign currency transactions by introducing global Fintech network. International Journal of Islamic and Middle Eastern Finance and Management, 14 (3), 506-523. https://doi.org/10.1108/imefm-01-2020-0035

Semko, R. (2019). Machine learning for robo-advisors: Testing for neurons specialization. Investment Management and Financial Innovations, 16 (4), 205-214. https://doi.org/10.21511/imfi.16(4).2019.18

Sharma, Z., & Zhu, Y. (2020). Platform building in initial coin offering market: Empirical evidence. Pacific-Basin Finance Journal, 61 . https://doi.org/10.1016/j.pacfin.2020.101318

Sheng, T. X. (2021). The effect of fintech on banks' credit provision to SMEs: Evidence from China. Finance Research Letters, 39 . https://doi.org/10.1016/j.frl.2020.101558

Shrestha, K. (2021). Multifractal detrended fluctuation analysis of return on bitcoin. International Review of Finance, 21 (1), 312-323. https://doi.org/10.1111/irfi.12256

Stulz, R. M. (2019). Fintech, Bigtech, and the future of banks. Journal of Applied Corporate Finance, 31 (4), 86-97. https://doi.org/10.1111/jacf.12378

Sybirianska, Y., Dyba, M., Britchenko, I., Ivashchenko, A., Vasylyshen, Y., & Polishchuk, Y. (2018). Fintech platforms in sme’s financing: eu experience and ways of their application in Ukraine. Investment Management and Financial Innovations, 15 (3), 83-96. https://doi.org/10.21511/imfi.15(3).2018.07

Takeda, F., Takeda, K., Takemura, T., & Ueda, R. (2021). The impact of information technology investment announcements on the market value of the Japanese regional banks. Finance Research Letters, 41 . https://doi.org/10.1016/j.frl.2020.101811

Tantri, P. (2021). Fintech for the poor: Financial intermediation without discrimination. Review of Finance, 25 (2), 561-593. https://doi.org/10.1093/rof/rfaa039

Tseng, P. L., & Guo, W. C. (2021). Fintech, credit market competition, and bank asset quality. Journal of Financial Services Research . https://doi.org/10.1007/s10693-021-00363-y

Uddin, A., & Yu, D. T. (2020). Latent factor model for asset pricing. Journal of Behavioral and Experimental Finance, 27 . https://doi.org/10.1016/j.jbef.2020.100353

Uddin, M. H., Mollah, S., & Ali, M. H. (2020). Does cyber tech spending matter for bank stability? International Review of Financial Analysis, 72 . https://doi.org/10.1016/j.irfa.2020.101587

Ullah, A., Pinglu, C., Ullah, S., Qian, N. Y., & Zaman, M. (2021). Impact of intellectual capital efficiency on financial stability in banks: Insights from an emerging economy abstract. International Journal of Finance & Economics . https://doi.org/10.1002/ijfe.2512

Vasenska, I., Dimitrov, P., Koyundzhiyska-Davidkova, B., Krastev, V., Durana, P., & Poulaki, I. (2021). Financial transactions using Fintech during the Covid-19 crisis in Bulgaria. Risks, 9 (3). https://doi.org/10.3390/risks9030048

Wang, R., Liu, J. T., & Luo, H. (2021). Fintech development and bank risk taking in China. European Journal of Finance, 27 (4-5), 397-418. https://doi.org/10.1080/1351847x.2020.1805782

Wang, Y., & Drabek, Z. (2021). Adverse selection in P2P lending: Does peer screening work efficiently?-Empirical evidence from a P2P platform. International Journal of Financial Studies, 9 (4). https://doi.org/10.3390/ijfs9040073

Yang, D., & Li, M. (2018). Evolutionary approaches and the construction of technology-driven regulations. Emerging Markets Finance and Trade, 54 (14), 3256-3271. https://doi.org/10.1080/1540496x.2018.1496422

Yang, W., Sui, X. P., & Qi, Z. (2021). Can fintech improve the efficiency of commercial banks?-An analysis based on big data. Research in International Business and Finance, 55 . https://doi.org/10.1016/j.ribaf.2020.101338

Yao, T., & Song, L. R. (2021). Fintech and the economic capital of Chinese commercial bank's risk: Based on theory and evidence. International Journal of Finance & Economics . https://doi.org/10.1002/ijfe.2528

Yao, Y. H., Li, J. P., & Sun, X. L. (2021). Measuring the risk of Chinese Fintech industry: Evidence from the stock index. Finance Research Letters, 39 . https://doi.org/10.1016/j.frl.2020.101564

Yehorycheva, S., Fysun, I., Hudz, T., Palchuk, O., & Boiko, N. (2020). Innovations in the insurance market of a developing country: Case of Ukraine. Investment Management and Financial Innovations, 17 (4), 175-188. https://doi.org/10.21511/imfi.17(4).2020.17

Zhang, A. L., Wang, S. Y., Liu, B., & Liu, P. (2020). How fintech impacts pre- and post-loan risk in Chinese commercial banks. International Journal of Finance & Economics . https://doi.org/10.1002/ijfe.2284

Zhang, X., & Wu, C. (2018). Continuous cash flow payment: Theories and practice framework. Emerging Markets Finance and Trade, 54 (4), 774-782. https://doi.org/10.1080/1540496x.2016.1241706

Zhao, X. J., Hou, W. X., An, J. F., Liu, X. D., & Zhang, Y. (2021). Initial coin offerings: What rights do investors have? European Journal of Finance, 27 (4-5), 305-320. https://doi.org/10.1080/1351847x.2020.1858130

Zhong, W. Q., & Jiang, T. F. (2021). Can internet finance alleviate the exclusiveness of traditional finance? Evidence from Chinese P2P lending markets. Finance Research Letters, 40 . https://doi.org/10.1016/j.frl.2020.101731

Zhou, X., & Chen, S. (2021). Fintech innovation regulation based on reputation theory with the participation of new media. Pacific-Basin Finance Journal, 67 . https://doi.org/10.1016/j.pacfin.2021.101565

Appendix 2 Sample of 70 Fintech IS articles

Alam, M. M., Awawdeh, A. E., & Bin Muhamad, A. I. (2021). Using e-wallet for business process development: Challenges and prospects in Malaysia. Business Process Management Journal, 27 (4), 1142-1162. https://doi.org/10.1108/bpmj-11-2020-0528

Alhassan, M. D., Kolog, E. A., & Boateng, R. (2020). Effect of gratification on user attitude and continuance use of mobile payment services: A developing country context. Journal of Systems and Information Technology, 22 (4), 353-380. https://doi.org/10.1108/JSIT-01-2020-0010

Alt, R., Beck, R., & Smits, M. T. (2018). Fintech and the transformation of the financial industry. Electronic Markets, 28 (3), 235-243. https://doi.org/10.1007/s12525-018-0310-9

Alyakoob, M., Rahman, M. S., & Wei, Z. Y. (2021). Where you live matters: local bank competition, online marketplace lending, and disparity in borrower benefits. Information Systems Research, 32 (4), 1390-1411. https://doi.org/10.1287/isre.2021.1043

Au, C. H., Tan, B. N., & Sun, Y. (2020). Developing a P2P lending platform: Stages, strategies and platform configurations. Internet Research, 30 (4), 1229-1249. https://doi.org/10.1108/intr-03-2019-0099

Barbu, C. M., Florea, D. L., Dabija, D. C., & Barbu, M. C. R. (2021). Customer experience in fintech. Journal of Theoretical and Applied Electronic Commerce Research, 16 (5), 1415-1433. https://doi.org/10.3390/jtaer16050080

Belanche, D., Casalo, L. V., & Flavian, C. (2019). Artificial intelligence in fintech: Understanding robo-advisors adoption among customers. Industrial Management & Data Systems, 119 (7), 1411-1430. https://doi.org/10.1108/imds-08-2018-0368

Bongomin, G. O. C., & Ntayi, J. M. (2020). Mobile money adoption and usage and financial inclusion: Mediating effect of digital consumer protection. Digital Policy Regulation and Governance, 22 (3), 157-176. https://doi.org/10.1108/dprg-01-2019-0005

Bunnell, L., Osei-Bryson, K. M., & Yoon, V. Y. (2020). FinPathlight: Framework for an multiagent recommender system designed to increase consumer financial capability. Decision Support Systems, 134 . https://doi.org/10.1016/j.dss.2020.113306

Burtch, G., Hong, Y. L., & Liu, D. (2018). The Role of provision points in online crowdfunding. Journal of Management Information Systems, 35 (1), 117-144. https://doi.org/10.1080/07421222.2018.1440764

Chatterjee, S., Sarker, S., Lee, M. J., Xiao, X., & Elbanna, A. (2021). A possible conceptualization of the information systems (IS) artifact: A general systems theory perspective(1). Information Systems Journal, 31 (4), 550-578. https://doi.org/10.1111/isj.12320

Chen, X. R., Hu, X. J., & Ben, S. L. (2021). How individual investors react to negative events in the fintech era? Evidence from China's peer-to-peer lending market. Journal of Theoretical and Applied Electronic Commerce Research, 16 (1), 52-70. https://doi.org/10.4067/s0718-18762021000100105

Coffie, C. P. K., Hongjiang, Z., Mensah, I. A., Kiconco, R., & Simon, A. E. O. (2021). Determinants of fintech payment services diffusion by SMEs in Sub-Saharan Africa: evidence from Ghana. Information Technology for Development, 27 (3), 539-560. https://doi.org/10.1080/02681102.2020.1840324

Cui, X., Liu, W., & He, Z. (2021). Attribute reduction algorithm of enterprise credit evaluation and its applications for web-based communities. International Journal of Web Based Communities, 17 (4), 293-304. https://doi.org/10.1504/IJWBC.2021.119473

Currie, W. L., Gozman, D. P., & Seddon, J. J. M. (2018). Dialectic tensions in the financial markets: A longitudinal study of pre- and post-crisis regulatory technology. Journal of Information Technology, 33 (4), 304-325. https://doi.org/10.1057/s41265-017-0047-5

Dehnert, M., & Schumann, J. (2022). Uncovering the digitalization impact on consumer decision-making for checking accounts in banking. Electronic Markets, 32 (3). https://doi.org/10.1007/s12525-022-00524-4

Dhar, V., & Stein, R. M. (2017). Economic and business dimensions fintech platforms and strategy. Communications of the Acm, 60 (10), 32-35. https://doi.org/10.1145/3132726

Du, K. (2018). Complacency, capabilities, and institutional pressure: Understanding financial institutions' participation in the nascent mobile payments ecosystem. Electronic Markets, 28 (3), 307-319. https://doi.org/10.1007/s12525-017-0267-0

Du, W. Y., Pan, S. L., Leidner, D. E., & Ying, W. C. (2019). Affordances, experimentation and actualization of fintech: A blockchain implementation study. Journal of Strategic Information Systems, 28 (1), 50-65. https://doi.org/10.1016/j.jsis.2018.10.002

Fu, R. S., Huang, Y., & Singh, P. V. (2021). Crowds, lending, machine, and bias. Information Systems Research, 32 (1), 72-92. https://doi.org/10.1287/isre.2020.0990

Gao, Z., Guo, Z., & Tang, Q. (2021). How do monetary incentives influence giving? An empirical investigation of matching subsidies on kiva. Information Systems and e-Business Management . https://doi.org/10.1007/s10257-021-00515-6

Ge, R. Y., Feng, J., Gu, B., & Zhang, P. Z. (2017). Predicting and deterring default with social media information in peer-to-peer lending. Journal of Management Information Systems, 34 (2), 401-424. https://doi.org/10.1080/07421222.2017.1334472

Gimpel, H., Rau, D., & Roglinger, 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

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

Gozman, D., Liebenau, J., & Mangan, J. (2018). The Innovation mechanisms of fintech start-ups: Insights from SWIFT's Innotribe competition. Journal of Management Information Systems, 35 (1), 145-179. https://doi.org/10.1080/07421222.2018.1440768

Haitao, S. (2020). Big data analysis of e-commerce loan risk of college students in the context of network finance. Information Systems and e-Business Management, 18 (3), 439-454. https://doi.org/10.1007/s10257-019-00424-9

Han, H., Teng, J., Xia, J. R., Wang, Y. H., Guo, Z. H., & Li, D. Q. (2021). Predict high-frequency trading marker via manifold learning. Knowledge-Based Systems, 213 . https://doi.org/10.1016/j.knosys.2020.106662

Hendershott, T., Zhang, X. Q., Zhao, J. L., & Zheng, Z. Q. (2021). Fintech as a game changer: Overview of research frontiers. Information Systems Research, 32 (1), 1-17. https://doi.org/10.1287/isre2021.0997

Hua, X. P., Huang, Y. P., & Zheng, Y. F. (2019). Current practices, new insights, and emerging trends of financial technologies. Industrial Management & Data Systems, 119 (7), 1401-1410. https://doi.org/10.1108/imds-08-2019-0431

Ilk, N., Shang, G. Z., Fan, S. K., & Zhao, J. L. (2021). Stability of transaction fees in BitCoin: a supply and demand perspective. MIS Quarterly, 45 (2), 563-592. https://doi.org/10.25300/misq/2021/15718

Jiang, Y., Ho, Y. C., Yan, X. B., & Tan, Y. (2018). Investor platform choice: Herding, platform attributes, and regulations. Journal of Management Information Systems, 35 (1), 86-116. https://doi.org/10.1080/07421222.2018.1440770

Jin, Y., Ding, C., Duan, Y., & Cheng, H. K. (2020). Click to success? The temporal effects of facebook likes on crowdfunding. Journal of the Association for Information Systems, 21 (5), 1191-1213. https://doi.org/10.17705/1jais.00634

Jinasena, D. N., Spanaki, K., Papadopoulos, T., & Balta, M. E. (2023). Success and failure retrospectives of fintech projects: A case study approach. Information Systems Frontiers . https://doi.org/10.1007/s10796-020-10079-4

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

Lagna, A., & Ravishankar, M. N. (2022). Making the world a better place with fintech research. Information Systems Journal, 32 (1), 61-102. https://doi.org/10.1111/isj.12333

Leong, C., Tan, B., Xiao, X., Tan, F. T. C., & Sun, Y. (2017). Nurturing a fintech ecosystem: The case of a youth microloan startup in China. International Journal of Information Management, 37 (2), 92-97. https://doi.org/10.1016/j.ijinfomgt.2016.11.006

Li, M. Y., Qin, Y., Liu, B., & Chu, X. W. (2021). Enhancing the efficiency and scalability of blockchain through probabilistic verification and clustering. Information Processing & Management, 58 (5). https://doi.org/10.1016/j.ipm.2021.102650

Lim, S. H., Kim, D. J., Hur, Y., & Park, K. (2019). An empirical study of the impacts of perceived security and knowledge on continuous intention to use mobile fintech payment services. International Journal of Human-Computer Interaction, 35 (10), 886-898. https://doi.org/10.1080/10447318.2018.1507132

Mai, F., Shan, Z., Bai, Q., Wang, X., & Chiang, R. H. L. (2018). How does social media impact Bitcoin value? A test of the silent majority hypothesis. Journal of Management Information Systems, 35 (1), 19-52. https://doi.org/10.1080/07421222.2018.1440774

Muthukannan, P., Tan, B., Gozman, D., & Johnson, L. (2020). The emergence of a fintech ecosystem: A case study of the Vizag fintech valley in India. Information & Management, 57 (8). https://doi.org/10.1016/j.im.2020.103385

Muthukannan, P., Tan, B., Tan, F. T., & Leong, C. (2021). Novel mechanisms of scalability of financial services in an emerging market context: Insights from Indonesian fintech Ecosystem. International Journal of Information Management, 61 . https://doi.org/10.1016/j.ijinfomgt.2021.102403

Nayak, B., Bhattacharyya, S. S., & Krishnamoorthy, B. (2019). Integrating wearable technology products and big data analytics in business strategy: A study of health insurance firms. Journal of Systems and Information Technology, 21 (2), 255-275. https://doi.org/10.1108/JSIT-08-2018-0109

Odoom, R., & Kosiba, J. P. (2020). Mobile money usage and continuance intention among micro enterprises in an emerging market – The mediating role of agent credibility. Journal of Systems and Information Technology, 22 (4), 97-117. https://doi.org/10.1108/JSIT-03-2019-0062

Ozili, P. K. (2020). Contesting digital finance for the poor. Digital Policy Regulation and Governance, 22 (2), 135-151. https://doi.org/10.1108/dprg-12-2019-0104

Pousttchi, K., & Dehnert, M. (2018). Exploring the digitalization impact on consumer decision-making in retail banking. Electronic Markets, 28 (3), 265-286. https://doi.org/10.1007/s12525-017-0283-0

Puschmann, T. (2017). Fintech. Business & Information Systems Engineering, 59 (1), 69-76. https://doi.org/10.1007/s12599-017-0464-6

Ryu, H. S. (2018). What makes users willing or hesitant to use fintech? The moderating effect of user type. Industrial Management & Data Systems, 118 (3), 541-569. https://doi.org/10.1108/imds-07-2017-0325

Saura, J. R., Reyes-Menendez, A., deMatos, N., & Correia, M. B. (2021). Identifying startups business opportunities from UGC on Twitter chatting: An exploratory analysis. Journal of Theoretical and Applied Electronic Commerce Research, 16 (6), 1929-1944. https://doi.org/10.3390/jtaer16060108

Senyo, P. K., Karanasios, S., Gozman, D., & Baba, M. (2022). Fintech ecosystem practices shaping financial inclusion: The case of mobile money in Ghana. European Journal of Information Systems, 31 (1), 112-127. https://doi.org/10.1080/0960085x.2021.1978342

Senyo, P. K., Osabutey, E. L. C., & Kan, K. A. S. (2021). Pathways to improving financial inclusion through mobile money: A fuzzy set qualitative comparative analysis. Information Technology & People, 34 (7), 1997-2017. https://doi.org/10.1108/itp-06-2020-0418

Shiau, W. L., Yuan, Y., Pu, X. D., Ray, S., & Chen, C. C. (2020). Understanding fintech continuance: Perspectives from self-efficacy and ECT-IS theories. Industrial Management & Data Systems, 120 (9), 1659-1689. https://doi.org/10.1108/imds-02-2020-0069

Stewart, H., & Jurjens, J. (2018). Data security and consumer trust in fintech innovation in Germany. Information and Computer Security, 26 (1), 109-128. https://doi.org/10.1108/ics-06-2017-0039

Stojanovic, B., Hofer-Schmitz, K., & Kleb, U. (2020). APT datasets and attack modeling for automated detection methods: A review. Computers & Security, 92 . https://doi.org/10.1016/j.cose.2020.101734

Tan, T. H., Zhang, Y., Heng, C. S. A., & Ge, C. M. (2021). Empowerment of grassroots consumers: A revelatory case of a Chinese fintech innovation. Journal of the Association for Information Systems, 22 (1), 179-203. https://doi.org/10.17705/1jais.00658

Tao, Q. Z., Dong, Y. Z., & Lin, Z. M. (2017). Who can get money? Evidence from the Chinese peer-to-peer lending platform. Information Systems Frontiers, 19 (3), 425-441. https://doi.org/10.1007/s10796-017-9751-5

Vo, A., Chapman, T. A., & Lee, Y. S. Examining Bitcoin and economic determinants: an evolutionary perspective. Journal of Computer Information Systems . https://doi.org/10.1080/08874417.2020.1865851

Vucetic, M., Brokesova, Z., Hudec, M., & Pastorakova, E. (2022). Financial literacy and psychological disaster preparedness: Applicability of approach based on fuzzy functional dependencies. Information Processing & Management, 59 (2). https://doi.org/10.1016/j.ipm.2021.102848

Wang, Z., & Ben, S. (2021). Effect of consumers’ online shopping on their investment in money market funds on ecommerce platforms. Information Systems and e-Business Management . https://doi.org/10.1007/s10257-021-00516-5

Wang, Z., Jiang, C. Q., & Zhao, H. M. (2021). Know where to invest: Platform risk evaluation in online lending. Information Systems Research . https://doi.org/10.1287/isre.2021.1083

Wang, Z. N., Guan, Z. Z., Hou, F. F., Li, B. Y., & Zhou, W. Y. (2019). What determines customers' continuance intention of fintech? Evidence from YuEbao. Industrial Management & Data Systems, 119 (8), 1625-1637. https://doi.org/10.1108/imds-01-2019-0011

Wessel, M., Gleasure, R., & Kauffman, R. J. (2021). Sustainability of rewards-based crowdfunding: a quasi-experimental analysis of funding targets and backer satisfaction. Journal of Management Information Systems, 38 (3), 612-646. https://doi.org/10.1080/07421222.2021.1987622

Wingreen, S. C., Kavanagh, D., Ennis, P. J., & Miscione, G. (2020). Sources of cryptocurrency value systems: the case of Bitcoin. International Journal of Electronic Commerce, 24 (4), 474-496. https://doi.org/10.1080/10864415.2020.1806469

Wu, M. E., Syu, J. H., Srivastava, G., & Lin, J. C. W. (2022). Informative index for investment based on Kelly criterion. Enterprise Information Systems . https://doi.org/10.1080/17517575.2021.1939425

Xie, J. L., Ye, L. Y., Huang, W., & Ye, M. (2021). Understanding fintech platform adoption: Impacts of perceived value and perceived risk. Journal of Theoretical and Applied Electronic Commerce Research, 16 (5), 1893-1911. https://doi.org/10.3390/jtaer16050106

Xie, P., Chen, H. L., & Hu, Y. J. (2020). Signal or noise in social media discussions: the role of network cohesion in predicting the Bitcoin market. Journal of Management Information Systems, 37 (4), 933-956. https://doi.org/10.1080/07421222.2020.1831762

Xu, Y. L., Bao, H. J., Zhang, W. Y., & Zhang, S. (2021). Which financial earmarking policy is more effective in promoting fintech innovation and regulation? Industrial Management & Data Systems, 121 (10), 2181-2206. https://doi.org/10.1108/imds-11-2020-0656

Yeh, J. Y., & Chen, C. H. (2022). A machine learning approach to predict the success of crowdfunding fintech project. Journal of Enterprise Information Management . https://doi.org/10.1108/jeim-01-2019-0017

Yun, J. J., Liu, Z., & Zhao, X. F. (2021). Introduction: Ambidextrous open innovation in the 4th industrial revolution. Science Technology and Society, 26 (2), 183-200. https://doi.org/10.1177/09717218211006969

Zhao, Y., & Chen, X. H. (2022). The relationship between the withdrawal of the digital economy's innovators, government interventions, the marketization level and market size based on big data. Journal of Enterprise Information Management . https://doi.org/10.1108/jeim-01-2021-0050

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Checkfirst raises $1.5M pre-seed to apply AI to remote inspections and audits

We’ve all seen them. The inspector with a clipboard, walking around a building, ticking off the last time the fire extinguishers were checked, or if all the lights are working. They work in the TICC (Testing, Inspection, Certification and Compliance) space, and they literally tick boxes. And while the job may seem simple enough to do physically, it’s a whole different ball game when it needs to be done remotely.

Founder Ben Lambert realized just that, when after moving to Portugal, his wife’s property inspection business needed to be run remotely. “It was no longer easy to check inspections on-site and get reliable information. A final report could take weeks to come through,” he told me. Plus, actually scheduling the inspections turned out to be at least as large a problem.

Seeing an opportunity, Lambert founded an AI-powered workflow tools startup, Checkfirst , that, in addition to allowing for remote inspections, enables businesses to schedule inspectors based on geographical location and qualifications. This results in less travel, a lower environmental footprint, and the workers end up happier as well. The company has now raised a pre-seed $1.5 million led by Lisbon-based, early-stage venture firm, Olisipo Way, and Hiero VC (a solo GP firm). Notion Capital, and angel investors from companies like Source Point, Busuu, Swogo and FaceIT also participated.

“As [the product] developed, we saw that the biggest problem wasn’t necessarily the data capture alone, but where companies earn or lose money was in the scheduling. It’s timely, as AI is perfect for scheduling tasks,” he said.

“The biggest problem in the industry is scheduling, and the cool thing is, with AI, you can schedule really easily,” he told me. “Say an inspector is in London but needs to be in Munich to audit a building. With AI, you can understand what they’re doing and put it all together. We’re creating a scheduling tool for all these big companies. It’s not just about meeting compliance; it’s also scheduling. Then the compliance tool allows them to collect data easily to meet the regulatory standards.”

It turns out that the TICC industry is moving people around the world all the time, explained Lambert.

“For example, an inspector could be in London today, but the company will send someone from Munich to London, because they don’t really understand they already have a guy in London. If an inspector then flies from Munich to London, they lose all of their margin immediately. With our tools, the guy the company was going to send in from Munich now doesn’t need to come to London. That saves the company thousands of euros, if not more.”

Lambert said they “initially used a mix of open source and commercial AI models”, and are now building their own “based on proprietary data for image recognition and scheduling”.

In terms of competitors, Checkfirst is going up against some large incumbents in the compliance space, such as Intact Systems, Lumiform, Safety Culture (a unicorn) and Happy Co (focuses on property management).

The difference with Checkfirst, says Lambert, is that it is an API-first solution and uses AI for image recognition and automation, churning out report summaries, and scheduling.

The startup is working with several clients on proof-of-concepts, one which has 30,000 customers, the company claims.

The co-founding team includes Lambert, CPO Oyvind Henriksen (who started Poq Studio) and CTO Rami Elsawy. Lambert was formerly with Nexmo and Agora.

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Danske Bank invests in United Fintech

Danske Bank has become the third institutional investor to invest in United Fintech, following in the footsteps of Citi and BNP Paribas.

United Fintech, an umbrella outfit dedicated to scooping up a stable of capital markets, wealth management and wholesale banking vendors, was founded in 2020 by CEO Christian Frahm. The firm has so far snapped up five fintechs, employing over 160 people across 8 countries. Firms acquired under the United Fintech roll up include Cobalt, FairXchange, TTMZero, Athena Systems and NetDania As part of the new financing deal, Danske Bank has secured a rotating board seat and will contribute to the platform’s strategic direction. Claus Harder, head of transaction banking & LC&I business development with Danske Bank, says: “Danske Bank...sees great opportunities as per both collaboration within the existing ecosystem of fintech companies, but also in being closer to the future fintech investment processes and decisions, where the partnership allows Danske Bank to expand its exposure to innovative solutions, ultimately benefiting our customer value proposition.” He says the investment will go a long way to support the Nordic bank's Forward ’28 strategy across areas such as corporate banking, capital markets, wealth management and API integrations: “The investment in United Fintech will generate possibilities to engage directly with fintechs that are subscale; to support their growth while simultaneously helping fuel our own digital transformation and growth strategy,” elaborates Harder. The investment comes just months after BNP Paribas and Citi entered as institutional investors in United Fintech.

United Fintech CEO Frahm says the firm expects to attract more leading institutions to the collaborative movement. Speaking of Danske Bank's involvement, Frahm says: "This commitment is instrumental in addressing the industry's most pressing challenges through collaboration, rather than isolated efforts. By uniting the strengths of Danske Bank and our other banking partners, we are setting the stage for a new era in banking where we move beyond traditional silos to propel the industry into the digital age.”

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According to the number of published articles, research articles contribute the most, while book chapters rank second. Table 1 shows that the topics of digital finance, FinTech, and e-finance constitute a modern knowledge field, especially since most studies have been completed in the last 3 years (2018, 2019, and 2020). Moreover, most of these ...
Fintech and financial sector: ADO analysis and future research agenda
However, within the existing body of literature, there is a notable limitation in the form of a comprehensive survey of fintech-related research. Ali, Ally, Clutterbuck, and Dwivedi (2020) reviewed 87 articles published between 2011 and 2019 to investigate blockchain-enabled economic benefits, challenges, and functionality. The findings ...
(PDF) Fintech, the new era of financial services
The research aims to fill the gap in the current academic literature regarding the appearance of innovation-focused financial technology (fintech) companies. The analysis provides a conceptual ...
Fintechs: A literature review and research agenda
In the Blockchain/Cryptocurrency sector of fintech activity Richter et al. (2015a) analyzed the advantages and disadvantages of virtual currencies in comparison with real money, but an important research article that addressed the intrinsic risks to the trading platforms of crypto coins, e.g. Bitcoin or Ether, was not identified. With respect ...
Full article: The rise and rise of financial technology: The good, the
The outline of this article is as follows. First, it has in this section briefly described the notion of fintech and the relevance of this study. Section 2 elaborates the approach and methodology used to conduct this investigation. Section 3 concentrates on analysing fintech research in the current literature.
Full article: How does the development of fintech affect financial
Table 6. , the development level of fintech has a U-shaped impact on financial efficiency, which is first inhibited and then promoted. The coefficient of the cross term of fintech and financial decentralisation (fdrfint) is significantly positive at the 1% level, indicating that the regression results are robust.
FinTech
FinTech is an international, peer-reviewed, open access journal on a variety of themes connected with financial technology, such as cryptocurrencies, risk management, robo-advising, crowdfunding, blockchain, new payment solutions, machine learning and AI for financial services, digital currencies, etc., published quarterly online by MDPI.. Open Access — free for readers, with article ...
Uncovering research trends and opportunities on FinTech: a
This paper employs the scientific econometric analysis approach to review 705 academic publications related to Fintech from 2006 to 2021. The historical evolution, latest status and development trend of FinTech research are identified by co-authorship networks, co-citation networks and timeline evolution. CiteSpace software is applied to conduct the literature analysis. The results show that ...
Fintech Innovations in the Financial Service Industry
The keywords used to retrieve research articles were "fintech innovations", "fintech regulations", "digital finance". Figure 2 explains that among 1023 articles those were retrieved, after removing duplicates, 772 records were eligible for the screening process. After general screening based on title and abstract, 346 records were ...
Perception, Adoption, and Pattern of Usage of FinTech Services by Bank
Consistent with the research results of Carlin, Olafsson, and Pagel (2017), it is found that the benefits of FinTech service is enjoyed more by the younger generation as compared with the baby boomers. Hence, it will be salient to improve awareness so that there is acceleration in the usage of FinTech services as it will reduce the cost of ...
How Fintech Is Driving Change And Five Benefits For Consumers
McKinsey's research underscores the rapid expansion of fintech, evident in the United States where nearly half of consumers utilized fintech products in 2021, notably peer-to-peer payment services ...
More Than 90% of Stablecoin Transactions Aren't Real, Study Finds
More than 90% of stablecoin transaction volumes aren't coming from genuine users, according to a new metric co-developed by Visa Inc., suggesting such crypto tokens may be far away from becoming ...
Fintech Stock Could Bounce Says Bull Signal
Shares of fintech firm Fidelity National Information Services Inc (NYSE:FIS) are trading at their highest level since February 2023 following a post-earnings gap higher on the charts.The equity also reclaimed support from its 50-day moving average after earnings, though the $76 level kept a lid on further gains.
Fintech: A content analysis of the finance and information systems
The amount of research related to financial technologies (fintech) has grown rapidly since these modalities have been implemented. A review of this literature base will help identify the topics that have been explored and identify topics for further research. This research project collects, synthesizes, and analyzes both the research strategies (i.e., methodologies) and content (e.g., topics ...
Checkfirst raises $1.5M pre-seed to apply AI to remote inspections and
Fintech UK challenger bank Monzo nabs another $190M as US expansion beckons. Paul Sawers. 5 hours ago. Monzo has raised another £150 million ($190 million), as the challenger bank looks to expand ...
Danske Bank invests in United Fintech
Sponsored: [New Report] The Future of UK Fintech: 2015 - 2035 - An IFGS Special Edition - UK Fintech Week 2024 News in your inbox For Finextra's free daily newsletter, breaking news and flashes ...