Credit Risk

Credit RiskTypes of LoansStandalone financing: When a FI is provided funds to a single client is known as stand along financing.Syndicated financing: When a group of FI is provided funds to a single client is known as syndicated financing.Secured loan: A loan that is backed by a first claim on certain assets (collateral) of the borrower if default occurs.Unsecured loan: A loan that only has a general claim to the assets of the borrower if default occurs.

5 Cs of CreditCharacterCapitalCapacityCollateralConditions

Calculating the return on a loanThe interest rate on the loan (BR);Any fees relating to the loan (f);The credit risk premium on the loan (m);The collateral backing of the loan; andOther nonprice terms [especially compensating balances (b) and reserve requirements(R)]

1 + k = 1 + f + (BR + m) 1+[b(1-R)]

Example Calculation of ROA on a LoanSuppose a bank does the following:Sets the loan rate on a prospective loan at 14 percent (where BR 12% and m 2%). Charges a 1/8 percent (or 0.125 percent) loan origination fee to the borrower. Imposes a 10 percent compensating balance requirement to be held as non-interest-bearing demand deposits. Sets aside reserves, at a rate of 10 percent of deposits, held at the Federal Reserve (i.e., the Feds cash-to-deposit reserve ratio is 10 percent).

1 + k = 1 + 0.00125 + (0.12 + 0.02) 1 [(0.10)(0.9)]

k = 15.52%

N U M E R I C A LMetrobank offers one-year loans with a 9% stated or base rate, charges a 0.25% loan origination fee, imposes a 10% compensating balance requirement, and must pay a 6% reserve requirement to the Federal Reserve. The loans typically are repaid at maturity. If the risk premium for a given customer is 2.5%, what is the simple promised interest return on the loan? What is the contractually promised gross return on the loan per dollar lent? Which of the fee items has the greatest impact on the gross return?

The Expected Return on a LoanThe promised return on the loan (1 + k ) that the borrower and lender contractually agree on includes both the loan interest rate and noninterest rate features such as fees. The promised return on the loan, however, may well differ from the expected and, indeed, actual return on a loan because of default risk. Default risk is the risk that the borrower is unable or unwilling to fulfill the terms promised under the loan contract. The Expected Return on a LoanDefault risk is usually present to some degree in all loans. Thus, at the time the loan is made, the expected return [ E ( r )] per dollar lent is related to the promised return as follows:1 + E(r) = p(1+k) + (1-p)0

where p is the probability of complete repayment of the loan (such that the FI receives the principal and interest as promised) and (1 - p) is the probability of default (in which the FI receives nothing, i.e., 0). Rearranging this equation, we get:E(r) = p(1 +k) - 1

To the extent that p is less than 1, default risk is present. This means the FI manager must (1) set the risk premium ( m ) sufficiently high to compensate for this risk and (2) recognize that setting high risk premiums as well as high fees and base rates may actually reduce the probability of repayment (p). That is, k and p are not independent. Indeed, over some range, as fees and loan rates increase, the probability that the borrower pays the promised return may decrease (i.e., k and p may be negatively related).

The Expected Return on a LoanFIs usually have to control for credit risk along two dimensions: the price or promised return dimension (1+k) and the quantity or credit availability dimension. Further, even after adjusting the loan rate (by increasing the risk premium on the loan) for the default risk of the borrower, there is no guarantee that the FI will actually receive the promised payments. The actual payment or default on a loan once it is issued may vary from the probability expected.

??Why could a lenders expected return be lower when the risk premium is increased on a loan? In addition to the risk premium, how can a lender increase the expected return on a wholesale loan? A retail loan?

An increase in risk premiums indicates a riskier pool of clients who are more likely to default by taking on riskier projects. This reduces the repayment probability and lowers the expected return to the lender. In both cases the lender often is able to charge fees that increase the return on the loan. However, in both cases also, the fees may become sufficiently high as to increase the risk of nonpayment of default on the loan.

??Why are most retail borrowers charged the same rate of interest, implying the same risk premium or class? What is credit rationing? How is it used to control credit risks with respect to retail and wholesale loans?

??Why are most retail borrowers charged the same rate of interest, implying the same risk premium or class? Most retail loans are small in size relative to the overall investment portfolio of an FI, and the cost of collecting information on household borrowers is high. As a result, most retail borrowers are charged the same rate of interest that implies the same level of risk. What is credit rationing? How is it used to control credit risks with respect to retail and wholesale loans?Credit rationing involves restricting the amount of loans that are available to individual borrowers. On the retail side, the amount of loans provided to borrowers may be determined solely by the proportion of loans desired in this category rather than price or interest rate differences, thus the actual credit quality of the individual borrowers. On the wholesale side, the FI may use both credit quantity and interest rates to control credit risk. Typically more risky borrowers are charged a higher risk premium to control credit risk. However, the expected returns from increasingly higher interest rates that reflect higher credit risk at some point will be offset by higher default rates. Thus rationing credit through quantity limits will occur at some interest rate level even though positive loan demand exists at even higher risk premiums.

??Why is the degree of collateral as specified in the loan agreement of importance to the lender? If the book value of the collateral is greater than or equal to the amount of the loan, is the credit risk of the lender fully covered? Why, or why not?

Collateral provides the lender with some assets that can be used against the amount of the loan in the case of default. However, collateral has value only to the extent of its market value, and thus a loan fully collateralized at book value may not be fully collateralized at market value. Further, errors in the recording of collateralized positions may limit or severely reduce the protected positions of a lender.

Default Risk ModelsQualitative modelsBorrower-specific factors:Reputation: Based on the lending history of the borrower; better reputation implies a lower risk premium.Leverage: A measure of the existing debt of the borrower; the larger the debt, the higher the risk premium.Volatility of earnings: The more stable the earnings, the lower the risk premium.Collateral: If collateral is offered, the risk premium is lower.Market-specific factors include:Business cycle: Lenders are less likely to lend if a recession is forecasted. Level of interest rates: A higher level of interest rates may lead to higher default rates, so lenders are more reluctant to lend under such conditions.

Credit Scoring ModelCredit scoring models are quantitative models that use observed borrower characteristics either to calculate a score representing the applicants probability of default or to sort borrowers into different default risk classes. By selecting and combining different economic and financial borrower characteristics, an FI manager may be able to:Numerically establish which factors are important in explaining default risk.Evaluate the relative degree or importance of these factors.Improve the pricing of default risk.Be better able to screen out bad loan applicants.Be in a better position to calculate any reserves needed to meet expected future loan losses.

Credit Scoring ModelThe primary benefit from credit scoring is that credit lenders can more accurately predict a borrowers performance without having to use more resources. With commercial loan, credit scoring models taking into account all necessary regulatory parameters and posting an 85% accuracy rate on average, according to credit scoring experts, 25 using these models means fewer defaults and write-offs for commercial loan lenders. To use credit scoring models, the manager must identify objective economic and financial measures of risk for any particular class of borrower. For consumer debt, the objective characteristics in a credit scoring model might include income, assets, age, occupation, and location. For commercial debt, cash flow information and financial ratios such as the debtequity ratio are usually key factors. After data are identified, a statistical technique quantifies, or scores, the default risk probability or default risk classification.Credit scoring models include these three broad types: (1) linear probability models, (2) logit models, and (3) linear discriminant analysis.

Linear Probability and Logit ModelExample 11-2Estimating the Probability of Repayment on a Loan Using Linear Probability Credit Scoring ModelsSuppose there were two factors influencing the past default behavior of borrowers: the leverage or debtequity ratio (D/E) and the salesasset ratio (S/A).

Based on past default (repayment) experience, the linear probability model is estimated as:

PDi = 0.5(D/Ei) + 0.1(S/Ai)

Assume a prospective borrower has a D/E .3 and an S/A 2.0. Its expected probability of default (PDi) can then be estimated as:

PDi = 0.5(.3) + 0.1(2.0) = 0.35

Linear Probability and Logit ModelWhile this technique is straightforward as long as current information on the Xij is available for the borrower, its major weakness is that the estimated probabilities of default can often lie outside the interval 0 to 1. The logit model overcomes this weakness by restricting the estimated range of default probabilities from the linear regression model to lie between 0 and 1. Essentially this is done by plugging the estimated value of PDi from the linear probability model (in our example, PDi = .35) into the following formula: F(PDi) = 1___ 1 + e-PDi

Linear Discriminant ModelsWhile linear probability and logit models project a value for the expected probability of default if a loan is made, discriminant models divide borrowers into high or low default risk classes contingent on their observed characteristics (Xj). Similar to these models, however, linear discriminant models use past data as inputs into a model to explain repayment experience on old loans. The relative importance of the factors used in explaining past repayment performance then forecasts whether the loan falls into the high or low default class.

Linear Discriminant ModelsAltmans discriminant function (credit-classification model) takes the form: Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5whereX1 = Working capital/total assets ratioX2 = Retained earnings/total assets ratioX3 = Earnings before interest and taxes/total assets ratioX4 = Market value of equity/book value of long-term debt ratioX5 = Sales/total assets ratio

According to Altmans credit scoring model, any firm with a Z score of less than 1.81 should be considered a high default risk firm; between 1.81 and 2.99, an indeterminant default risk firm; and greater than 2.99, a low default risk firm.Example 11-3Calculations of Altmans Z-ScoreSuppose that the financial ratios of a potential borrowing firm took the following values:X1 = 0.2, X2 = 0, X3 = 0.20, X4 = 0.10, X5 = 2.0

The ratio X2 is zero and X3 is negative, indicating that the firm has had negative earnings or losses in recent periods. Also, X4 indicates that the borrower is highly leveraged. However, the working capital ratio (X1) and the sales/assets ratio (X5) indicate that the firm is reasonably liquid and is maintaining its sales volume. The Z score provides an overall score or indicator of the borrowers credit risk since it combines and weights these five factors according to their past importance in explaining borrower default. For the borrower in question:

Z = 1.2(.2) + 1.4(0) + 3.3(.20) + 0.6(.10) + 1.0(2.0) = 1.64

With a Z score less than 1.81 (i.e., in the high default risk region), the FI should not make a loan to this borrower until it improves its earnings.??What are the purposes of credit scoring models? How do these models assist an FI manager in better administering credit?

Credit scoring models are used to calculate the probability of default or to sort borrowers into different default risk classes. The primary benefit is to improve the accuracy of predicting borrowers performance without using additional resources. This benefit results in fewer defaults and charge offs to the FI.

The models use data on observed economic and financial borrower characteristics to assist an FI manager in (a) identifying factors of importance in explaining default risk, (b) evaluating the relative degree of importance of these factors, (c) improving the pricing of default risk, (d) screening bad loan applicants, and (e) more efficiently calculating the necessary reserves to protect against future loan losses.??Suppose the estimated linear probability model is PD = .3X1 + .2X2 0.5X3 + error, where X1 = 0.75 is the borrowers debt/equity ratio, X2 = 0.25 is the volatility of borrower earnings, and X3 = 0.10 is the borrowers profit ratio.What is the projected probability of default for the borrower?What is the projected probability of repayment if the debtequity ratio is 2.5?What is a major weakness of the linear probability model???Describe how a linear discriminant analysis model works. Identify and discuss the criticisms which have been made regarding the use of this type of model to make credit risk evaluations.Linear discriminant models divide borrowers into high or low default classes contingent on their observed characteristics. The overall measure of default risk classification (Z) depends on the values of various financial ratios and the weighted importance of these ratios based on the past or observed experience. These weights are derived from a discriminant analysis model.

Several criticisms have been levied against these types of models. First, the models identify only two extreme categories of risk, default or no default. The real world considers several categories of default severity. Second, The relative weights of the variables may change over time. Further, the actual variables to be included in the model may change over time. Third, hard to define, but potentially important, qualitative variables are omitted from the analysis. Fourth, the real-world database of defaulted loans is very incomplete. Finally, the model is very sensitive to changes in variables. A change in sales of 40 percent may cause the model to provide different accept/reject decisions, but a decrease in sales in the real world normally is not seen as hard evidence that credit should be denied or withdrawn from an otherwise successful company.

??MNO, Inc., a publicly traded manufacturing firm in the United States, has provided the following financial information in its application for a loan. All numbers are in thousands of dollars.

Also assume sales $500, cost of goods sold $360, taxes $56, interest payments $40, net income $44, the dividend payout ratio is 50 percent, and the market value of equity is equal to the book value.What is the Altman discriminant function value for MNO, Inc.? Should you approve MNO, Inc.s, application to your bank for a $500 capital expansion loan?If sales for MNO were $300, the market value of equity was only half of book value, and the cost of goods sold and interest were unchanged, what would be the net income for MNO? Assume the tax credit can be used to offset other tax liabilities incurred by other divisions of the firm. Would your credit decision change?Would the discriminant function change for firms in different industries? Would the function be different for retail lending in different geographic sections of the country? What are the implications for the use of these types of models by FIs?AssetsLiabilitiesCash$20Accounts payable$30Accounts receivables90Notes payable90Inventory90Accruals30Long-term debt150Plant and equipment500Equity400 Total assets$700 Total liab. + equity$700??Consider the coefficients of Altmans Z score. Can you tell by the size of the coefficients which ratio appears most important in assessing creditworthiness of a loan applicant? Explain.

Although X3, or EBIT/total assets has the highest coefficient (3.3), it is not necessarily the most important variable. Since the value of X3 is likely to be small, the product of 3.3 and X3 may be quite small. For some firms, particularly those in the retail business, the asset turnover ratio, X5 may be quite large and the product of the X5 coefficient (1.0) and X5 may be substantially larger than the corresponding number for X3. Generally, the factor that adds most to the Z score varies from firm to firm and industry to industry.

??If the rate of one-year T-Bills currently is 6 percent, what is the repayment probability for each of the following two securities? Assume that if the loan is defaulted, no payments are expected. What is the market-determined risk premium for the corresponding probability of default for each security?

One-year AA rated bond yielding 9.5 percent?One-year BB rated bond yielding 13.5 percent?

??A bank has made a loan charging a base lending rate of 10 percent. It expects a probability of default of 5 percent. If the loan is defaulted, it expects to recover 50 percent of its money through the sale of its collateral. What is the expected return on this loan???Assume that a one-year T-bill is currently yielding 5.5 percent and an AAA rated discount bond with similar maturity is yielding 8.5 percent.If the expected recovery from collateral in the event of default is 50 percent of principal and interest, what is the probability of repayment of the AAA rated bond? What is the probability of default?What is the probability of repayment of the AAA-rated bond if the expected recovery from collateral in the case of default is 94.47 percent of principal and interest? What is the probability of default?What is the relationship between the probability of default and the proportion of principal and interest that may be recovered in case of default on the loan?RAROC ModelsAn increasingly popular model used to evaluate (and price) credit risk based on market data is the RAROC model. The RAROC (risk-adjusted return on capital) was pioneered by Bankers Trust (acquired by Deutsche Bank in 1998) and has now been adopted by virtually all the large banks. The essential idea behind RAROC is that rather than evaluating the actual or contractually promised annual ROA on a loan, the lending officer balances expected interest and fee income less the cost of funds against the loans expected risk. RAROC ModelsFurther, rather than dividing annual loan income by assets lent, it is divided by some measure of asset (loan) risk or what is often called capital at risk, since (unexpected) loan losses have to be written off against an FIs capital:

RAROC = One year net income on a loan Loan (asset) risk or capital at risk

A loan is approved only if RAROC is sufficiently high relative to a benchmark return on capital (ROE) for the FI, where ROE measures the return stockholders require on their equity investment in the FI. RAROC ModelsThe idea here is that a loan should be made only if the risk-adjusted return on the loan adds to the FIs equity value as measured by the ROE required by the FIs stockholders. Thus, for example, if an FIs ROE is 15 percent, a loan should be made only if the estimated RAROC is higher than the 15 percent required by the FIs stockholders as a reward for their investment in the FI. Alternatively, if the RAROC on an existing loan falls below an FIs RAROC benchmark, the lending officer should seek to adjust the loans terms to make it profitable again. Therefore, RAROC serves as both a credit risk measure and a loan pricing tool for the FI manager.The numerator of the RAROC equation is relatively straightforward to estimate. Specifically,One year net income on loan = (Spread + Fees) x Dollar value of the loan outstanding??A bank is planning to make a loan of $5,000,000 to a firm in the steel industry. It expects to charge a servicing fee of 50 basis points. The loan has a maturity of 8 years with a duration of 7.5 years. The cost of funds (the RAROC benchmark) for the bank is 10 percent. Assume the bank has estimated the maximum change in the risk premium on the steel manufacturing sector to be approximately 4.2 percent, based on two years of historical data. The current market interest rate for loans in this sector is 12 percent.Using the RAROC model, determine whether the bank should make the loan.What should be the duration in order for this loan to be approved?Assuming that the duration cannot be changed, how much additional interest and fee income will be necessary to make the loan acceptable?Given the proposed income stream and the negotiated duration, what adjustment in the loan rate would be necessary to make the loan acceptable?Internal Credit Risk Rating SystemObligor Rating Facility RatingA. Financial Condition including: a. Economic and financial situation b. Leverage c. Profitability d. Cash flows B. Management and ownership structure a. Ownership structure b. Management and quality of internal controls c. Promptness/ assessment of the willingness to pay d. Strength of Sponsors A. Facility a. Nature and purpose of loan b. Loan structure c. Product type d. Priority of rights in case of bankruptcy e. Degree of collateralization f. Composition of collateral Internal Credit Risk Rating SystemObligor Rating Facility RatingC. Qualitative factors: a. CIB report b. Sector of business c. Industry properties and its future prospects D. Others: a. Country risk b. Comparison to external ratings. c. Credit information from other sourcesB. Collateral a. Nature b. Quality c. Liquidity d. Market value e. Exposure of the collateral to different risks f. Quality of the charge

How to measure efficiency of banksGross profit / Loss as percentage of total assetsNet profit/ Loss as percentage of total assetsSpread as percentage of total assets Business per employeeReturn on assetsNet profit per employee percentNon-performing assets