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Credit Risk Management

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Credit Risk Management

Jul 16, 2013

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Credit Risk Management. Chapters 11 & 12. Credit Risk Management. uniqueness of FIs as asset transformers What do we mean? What type of risk do FIs incur due to this role? What are important things FIs must do to deal with/reduce these risks?

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• gross debt service ratio
• necessary information
• credit scoring models
• secondary market forces standardization

Presentation Transcript

Credit Risk Management Chapters 11 & 12

Credit Risk Management • uniqueness of FIs as asset transformers • What do we mean? • What type of risk do FIs incur due to this role? • What are important things FIs must do to deal with/reduce these risks? • importance of sound banking system for economic health • Japan • US credit problems in 1980s and 1990s

Credit Analysis • all analysis should be geared to one decision • Does FI grant the loan or not? • stated loan policy • clear documentation • criteria not discriminatory • minimum credit standards • standard application forms

Types of Loans • Commercial and Industrial loans • maturities • uses • amounts • syndicated loans • secured or unsecured • spot/loan commitment • importance of commercial paper

Types of Loans • Real Estate loans • mortgage loans and home equity loans • commercial vs. residential mortgage loans • ARMs • Consumer loans • i.e., personal or auto loans • revolving loan • usury ceilings

Real Estate Lending • large secondary market forces standardization of applications • major factors in accept/reject decision • applicant’s ability and willingness to repay • value of borrower’s collateral • characteristics/standards used to assess requirements

Real Estate Lending • GDS (gross debt service) ratio - gross debt service ratio calculated as total accommodation expenses (mortgage, lease, condominium, management fees, real estate taxes, etc.) divided by gross income • TDS (total debt service) ratio - total debt ratio calculated as total accommodation expenses plus all other debt service payments divided by gross income

Credit Scoring • expresses applicant’s credit quality numerically – removes some subjectivity • helps FI manager: • numerically establish which factors are important in explaining default risk • evaluate the relative importance of factors • improve pricing of default risk • be better able to screen out bad loan applicants • be in better position to calculate any reserves needed to meet expected future loan losses

Credit Analysis • Consumer and Small Business lending • Mid-Market Commercial and Industrial • firms with annual sales of about $5-$100 million • subjective and objective in evaluation

Credit Scoring Models • linear probability and logit models • use past data as inputs into model to explain repayment experience on old loans • relative importance of factors in explaining past repayment is used to forecast repayment probabilities of new loans • Linear discriminant models • while above models project a value for expected probability of default if a loan is made, discriminant models divide borrowers into high or low default risk classes contingent on observed characteristics • Altman’s Z • Z = 1.2X1 + 1.4x2 + 3.3x3 + 0.6x4 + 1.0x5 • X1 = working capital / total assets X2 = RE / total assets • X3 = EBIT / total assets X4 = MV equity / BV LT debt • X5 = sales / total assets

The KMV Model • Banks can use the theory of option pricing to assess the credit risk of a corporate borrower • The probability of default is positively related to: • the volatility of the firm’s stock • the firm’s leverage • A model developed by KMV corporation is being widely used by banks for this purpose

Return on Loan • methods to calculate • ROA (return on assets) • RAROC (risk-adjusted return on capital) • factors that affect FI’s return on loan: • The base lending rate on the loan (L) • The credit risk premium (m) • Fees earned as a result of the loan (e.g. origination fee and credit line fees) • Whether the borrower repays in full on time • The value of collateral and ease and cost of collections if the borrower defaults • The nonprice terms and conditions on the loan (other than fees): • Origination fee (f) • Compensating balances (b) • Reserve requirements (R)

ROA • ROA per dollar lent by FI is • ROA per $ lent is going to be greater than simple promised interest return on loan if b>0 because FI gets to keep compensating balance

Example 1 • A bank has a base lending rate of 8% (L), and charges a certain customer a 110 basis point risk premium (m). The bank also charges a 1% origination fee (f). The bank requires the borrower to maintain compensating balances of 7% of the loan amount. The reserve requirement is 10% and the loan amount is $1 million.

Example 2 • A corporate customer obtains a $1 million line of credit from a bank. The customer agrees to pay a 9% interest rate and agrees to make compensating balances of 6% of the total credit line and 3% of the amount actually borrowed. These will be held in non-interest bearing transactions deposits at the bank for one year. The bank charges a 1% loan origination fee on the amount borrowed and a 0.25% commitment fee on the unused line of credit. The expected draw down (loan amount) is 60% of the line for one year. Reserve requirements are 10%. What is the expected rate of return to the bank?

Example 3 • The credit risk premium (m) can be set based on historical default rates on loans of this category and rates of return on defaulted loans. For instance in order to earn the base loan rate of say 9% if the default history of a given loan category is as follows: • % of loans Default experience RoR on category • 98% No default 9% + m • 1.5% Limited default 0%[1] • 0.5% Total writeoff -100% • [1] The percent of loans and the rates of return numbers should both be net of recoveries

RAROC • The risk adjusted return on capital (RAROC) originated by Banker’s Trust is now widely used instead of the ROA method of loan pricing presented above.

Example 4 • Continuing with Example 1 from above and adding the additional necessary information will illustrate how to calculate the RAROC: • The loan had income of $101,000. Suppose the dollar cost rate (including interest and noninterest costs) of providing the loan is 10.3%. The net loan amount was $937,000 so the dollar cost is thus $96,511 (=$937,000  0.103). • Suppose that typical default rates may be 0.3% in a given year. However, according to historical default rates, the 99th percentile, or the extreme loss rate, for this loan category is 3%.[1] This means that the bank believes that in the worst case scenario (which in this case should happen only once every hundred years), 3% of the loans will default instead of the typical 0.3%. • Suppose further that based on historical data the bank can expect to eventually recover 25% of the loans that default.

Loan Portfolio Risk • credit scoring and RAROC and other methods helped FI analyze risk of individual loan • also need to measure credit risk to entire loan portfolio • simple models of loan concentration risk • migration analysis • concentration limits

Concentration Limits • external limits set on the maximum loan size that can be made to an individual borrower • set limits by assessing the borrower’s current portfolio, its operating unit’s business plans, its economists’ economic projections, and its strategic plans

Example 5 • Suppose management is unwilling to permit losses exceeding 10% of an FI’s capital to a particular sector. If management estimates that the amount lost per dollar of defaulted loans in this sector is 40 cents, the maximum loans to a single sector as a percent of capital, defined as the concentration limit, is • CL = maximum loss as % of capital * (1/loss rate) = 10% * (1/0.4) = 25%

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Credit Risk Management - PowerPoint PPT Presentation

Credit Risk Management

... and lines of credit as well as personal term loans and leases instalment loans, auto loans annd leases, student and educational loans, personal finance, ... – powerpoint ppt presentation.

• What is Integrated Risk Management?
• Measure, monitor and manage all the risks across the bank.
• Bank wide integrated risk management infrastructure in terms of people, policies and systems
• Common and consistent risk measurement and quantification methodologies across all risk categories
• Aggregation of risks and estimation of economic capital to assist in risk/ return decision making
• Facilitates strategic value creation
• Key to regulatory compliance
• Mechanism for efficient allocation of economic capital
• Enables bank to maximise returns
• Lower capital costs
• Better decision making due to scenario analysis
• Risk adjusted pricing
• Loss reduction due to understanding of correlations
• Elimination of unwanted exposures
• Credit Risk
• Probability of Default
• Loss Given Default
• Exposure at Default
• Market Risk
• Trading Book (VaR)
• Interest Rate Risk on Banking Book
• Operational Risk (evolving)
• Modelling correlations requires data and is not easy
• Fat tails in credit risk create problems
• Under the IRB approach, banks must categorise banking-book exposures into broad classes of assets with different underlying risk characteristics, subject to the defitinitions set out below.
• The asset classes are corporate, sovereign, bank, retail and equity
• Within the corporate assets class 5 sub classes of specialised lending are separately identified.
• Within the retail asset class 3 sub classes are separetly identified
• Project finance
• Object finance
• Commodities finance
• Income producing real estate
• High volatility commercial real estate
• Exposures to individuals (such as revolving credits and lines of credit as well as personal term loans and leases instalment loans, auto loans annd leases, student and educational loans, personal finance, and other exposures with similar characteristics)
• Residential mortgage loans (including first and subsequent lines, term loans and revolving home equity lines of credit)
• Loans extended to small business and managed as retail exposures less than 1 mill euro
• THE CREDIT REVIEW ASSESSMENT OF CAPITAL ADEQUACY, AT A MINIMUM, SHOULD COVER FOUR AREAS
• Risk rating systems
• Portfolio analysis/aggregation
• Securitization/complex credit derivatives
• Large exposures and risk concentration
• Loan reviews
• Exposure monitoring
• Portfolio reporting
• -Quality of
• financial data
• -Analytical tools
• -Firm size/value
• facility/LIED
• ongoing review by initial
• -periodic review of each
• customer relationship
• -aimed at reviewing
• profitability/desirability
• as well as condition
• -generally conducted by
• same authorities that
• approve loans
• -Quartely process focused
• on loans that exibit current
• or prospective problems
• Aimed at identifying best
• path to improve or exit credit
• at lowest cost
• -Conducted by same
• authorities to improve loans
• although others may
• participate as well (work
• -Review of adequacy of
• underwriting and
• monitoring from random
• -sample weighted toward
• higer risk loans
• -loan review judgement is
• negative consequences
• for initial rater if
• consistent disagreements
• Increased reliance on objective risk assessment
• Credit process differentiated on the basis of risk, not size
• Investment in workflow automation / back-end processes
• Align Risk strategy Business Strategy
• Active Credit Portfolio Management
• Credit Credit Risk Policies should be comprehensive
• Credit organisation - Independent set of people for Credit function Risk function / Credit function Client Relations
• Set Limits On Different Parameters
• Separate Internal Models for each borrower category and mapping of scales to a common scale
• Ability to Calculate a Probability of Default based on the Internal Score assigned
• Quantitative model to predict default risk dynamically
• Model is constructed by using the hybrid approach of combining Factor model Structural model (market based measure)
• The inputs used include Financial ratios, default statistics, Capital Structure Equity Prices.
• The present coverage include listed Crisil rated companies
• The product development work related to private firm model portfolio management model is in process
• The model is validated internally
• The most complicated product developed and with the help of in-house technology.
• Derivation of Asset value volatility
• Calculated from Equity Value , volatility for each company-year
• Solving for firm Asset Value Asset Volatility simultaneously from 2 eqns. relating it to equity value and volatility
• Calculate Distance to Default
• Calculate default point (Debt liabilities for given horizon value)
• Simulate the asset value and Volatility at horizon
• Calculate Default probability (EDF)
• Relating distance to default to actual default experience
• Use QRM Transition Matrix
• Calculate Default probability based on Financials
• Arrive at a combined measure of Default using both
• Credit culture refers to an implicit understanding among bank personnel that certain standards of underwriting and loan management must be maintained.
• Strong incentives for the individual most responsible for negotiating with the borrower to assess risk properly
• Sophisticated modelling and analysis introduce pressure for architecuture involving finer distinctions of risk
• Strong review process aim to identify and discipline among relationship managers

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