1. Fin 129 Financial Institutions Management
Credit Risk
Fin 129
Financial Institutions Management

2. Assessment of Credit Risk
FI manager must be able to:
Price Loan correctly based upon risk
evaluate possibility of default and make sure total risk limits are not violated

3. Credit Quality Recent concern over the quality of credit:
Rapid growth in loans (over 10% a year in the late 1990’s
Commercial Real Estate Loans
Low-quality auto loans
Credit cards
Impact on charge offs
Since 1991, the ratio of nonperfoming loans (90 days past due) has actually increased while growth has increased.

4. Commercial and Industrial Loans
Syndicated Loan -- provided by a group of FI’s instead of an individual lender -- spreads risk
Secured Loan - backed by specific assets
Unsecured Loan - only a general claim on assets
Spot Loan --borrower takes entire amount at one point in time in contrast to a loan commitment
Commercial paper -- short term unsecured borrowing by firms

5. Real Estate Loans Mainly Mortgage Loans Adjustable Rate Mortgages
creates prepayment risk and default risk.
Adjustable Rate Mortgages
interest rate is adjusted periodically.

6. Consumer Loans Credit Card loans
Revolving Credit- Open line of credit where the borrower can borrow and repay at will
Usury Ceilings -- maximum rate that an FI can charge on consumer and mortgage debt

7. Credit Analysis Essentially default risk analysis
investigating the borrowers
Evaluating Credit risk inherent in the operations of the business (or activities of the individual)?
What can be done by the borrower to lower the risk?
How can the lender control and structure the risk? (execution and administration of loan)

8. Evaluating Credit Risk the 5 c’s +1
Character --
Capacity --
Capital --
Conditions –
Collateral --
Cash --
Which of the characteristics is the most important?

9. Evaluating the 5 c’s Character
Based upon reputation of firm and past borrowing experience with the lender.
Creates an implicit contract that guarantees loans will be made and repaid
Works to the disadvantage of small and first time lenders
Capacity
Does the representative have the legal ability to commit the firms resources

10. Evaluating the 5 c’s Capital
Borrowers wealth position and can it withstand changes in economic conditions
Look at simple ratio analysis, Debt equity ratio
Volatility of earnings - more volatility implies higher probability of default
(Cash)
Liquidity of capital

11. Evaluating the 5 c’s Conditions
Market Specific Factors, common to all firms
Current phase of business cycle and relation to business of firm
Collateral
What assets can be pledged to secure the loan?
Are claims on assets senior to other claims?

12. Stages of Credit Evaluation Historical Perspective
Overview of management & operations
Business and industry outlook report
i.e. competitors, suppliers (conditions)
Background info (character)
Common size financial ratio analysis
compare to industry averages (liquidity, leverage, profitability) (capital, collateral, cash)
Analysis of cash flows (capital and cash)
Cash based income statement,
Investigate sources and uses of cash

13. Stages of Credit Evaluation
First three provide historical perspective -- then look at future
Projections of borrowers financial condition
Pro forma Financial Statements
Attempt to provide an objective outlook at the future prospects
Run sensitivity and Scenario Analysis on the projections

14. Credit Execution and Administration
Loan Covenants
Specific requirements either party must adhere to
Affirmative requires borrower to take certain actions (Maintain liquidity position)
Negative -- restricts the borrower from certain actions (acquiring more debt)
Credit Review
Review outstanding loans and monitor problems loans

15. Credit Execution and Administration
Default Scenarios
What actions (or inactions) would constitute default
Who is responsible for collection costs, attorney fees etc…
What actions the are the lender legally allowed to take.

16. Credit Execution and Administration
Documentation
Collateral needs to be “perfected” -- FI wants to have senior claims
Position Limits
The maximum amount of allowable credit to a single borrower
Risk Rating
FI can grade (rank) individual loans and counter parties (we explain how soon)

17. The 5 bad c’s the FI should avoid
Complacency -- assumes that since things were good in the past
Carelessness -- Poor underwriting techniques
Communication -- Loan policy needs to be communicated to loan officers and enforced
Contingencies -- tendency to downplay or ignore
Competition -- Following changes in competitors practices instead of following own policies.

18. Evaluating Credit Risk Credit Scoring Models
Quantitative models that use observable characteristics to score or rank borrowers based on probability of default.
Credit scoring provides a measure of the possibility of default based upon characteristics of borrowers.
Characteristics cannot be prohibited info (antidiscrimination laws - sex, race, not included) and must be statistically justified in relation to default risk.

19. Credit Scoring Models Linear Probability and Logit Models
Uses historical data to explain the repayment experience of old loans.
Divide loans into two categories those that did default (prob of default =1) and those that did not default (prob of default = 0)

20. Linear Prob. and Logit models
For the given set of variables the following regression can be estimated:

21. Linear Prob and Logit Models
Given the estimated values of Bj, you can take the loan applicants current values often variables and estimate the expected probability of default Z.

22. Linear Prob and Logit Models
Strengths
Weaknesses
Use of logit solves this

23. Liner Discriminate Credit Scoring Models
Divides borrowers into risk classes based upon aggregate score, does not estimate
For each observable variable, a weight is determined based upon past experience of loans.
Then an aggregate value is calculated and the loans are separated by the high or low probability of default.

24. A second version
Points assigned based on characteristic and past experience (For example length of time in current job (more than a year add 5, less than a year add 2). Then Aggregate score is calculated.

25. Fico Scores
Most credit scores in the US are calculated by software developed by Fair Issac and Company
There are three main providers of credit scores: Equifax, Experian and TransUnion
Most lending institutions will obtain scores from multiple services when evaluating credit risk.

26. Distribution of Fico Scores*
Source .com

27. Fico Score Comparison Score Rate Spread Additional Cost 720-850 5.783
$150, year fixed rate mortgage national averages
Score
Rate
Spread
Additional Cost
5.783
5.903
.125
$4,308
6.446
.663
$23,139
7.596
1.813
$64,870
8.531
2.74
$100,138
9.289
3.506
$129,139
source

29. Payment History Payment Info on specific types of accounts
Public Records (bankruptcy, suits, wage adjustments, past due items, etc.)
Severity of past delinquencies
Time since delinquency or poor public rec.
Number of

30. Amounts Owed Total amount owed on accounts
Amount owed on specific accounts
Lack of a specific type of balance
Proportion of

31. Length of Credit History
Time since account opened
Time since account opened, by type of account
Time since account activity

32. New Credit
Number of recently opened accounts and proportion of accounts recently opened by type
Number of recent credit inquiries
Time since recent account openings by type
Time since credit inquiry
Re-establishment of positive credit history following past problems

33. Type of credit used
Number of (presence, prevalence, and recent info on) various types of accounts (credit cards, installment loans, mortgage etc)

34. Note
The same factors may impact different applicants in different ways. Some factors may be more or less important depending upon the other factors.
No one piece of info will determine your score.

35. Not in your credit score
Race, age, religion, nationality, sex, marital status (Regulation B)
Salary, Occupation, title, employer, date employed, employment history
Location
Rates charged on outstanding credit
Child/family support obligations and rental agreements.

36. Average Credit Statistics
Number of Obligations: 11, 7 credit cards, 4 installment loans
Past Payment Performance: 4/10 30 days late or greater 2/10 60 days late or later, 85% never had loan 90+days overdue.
Credit Utilization:
Credit Cards 48%<$ % < 10% > $10,000
Total (less mortgages) 54% < $5,000, 30% > $10,000

37. Average Credit Statistics
Total Available Credit: $12,190 combined on all credit cards, 1/8 uses more than 80% of available credit, over 50% use less than 30% of available credit
Length of Credit History: average 12 years1 in 5 have histories over 20 years, 1 in 20 shorter than 2 years
Inquires: one a year average, less than 7% have more than 4 inquiries in past year.

38. Problems with Credit Scoring Models in general
Limited number of cases (in the extreme only two are considered - default no default)
No obvious economic reason that future will reflect the past. Need to adjust the model constantly to account for possible changes
Ignores some relationships such as borrower lender relationships.
No centralized database of business loans to provide measure of market risk.

39. Newer Models of Credit Risk
Term Structure Approaches
Mortality Rate Approaches
RAROC models
Option Models
Credit Metrics
Credit Risk +

40. Term structure approaches
The goal of a term structure approach is to derive the probability of default from observed differences in yield (risk premiums).
Construct zero coupon treasury yield curves and zero coupon corporate curves for similar rated debt.
Look at risk premium for a given maturity.

41. Term structure approaches
Assume that the yield on the low grade bond is 8% and the yield on the treasury is 5%.
If an investor is indifferent between the two options it implies that the expected return on the risky asset equals the return on the risk free asset or
p(1+k) = (1+i)
where p = probability of no default,
k = return on risky asset, i = return on treasury

42. Term structure approaches
Assume that k = 8% and i = 5% then the implied probability of no default, p, is found by:

43. Term structure approaches
If the loan is perceived to have a = or 2.77% probability of default it should have a risk premium set equal to 3%.
Can be extended to account for a partial recovery of principle and interest in the case of default. Let g represent the proportion of the loan that is recoverable
(1-p)g(1+k) +p(1+k) =(1+i)
This can also be extended to the case of multi period debt instruments

44. Term structure approaches
For multiperiod debt instruments you need to calculate the marginal probability of default for each time period then aggregate this into a cumulative probability of default.
Using the forward rate and the cumulative probability, an expected probability (or implied) probability of default can be found.

45. Marginal Mortality Rate
The marginal mortality rate of the loan is the probability of the of the loan defaulting in a given year of issue

46. RAROC Models Risk Adjusted Return on Capital Models
Income should be adjusted for fees and interest spread

47. RAROC
The most difficult part of the analysis is finding the capital at risk.
One approach would be to use duration.

48. CreditMetrics and Credit Risk +
Uses value at risk to find the possible loss on the loan portfolio given the assumption of “a bad” outcome over the given time period.
Credit Risk +
Similar to Value at Risk
Calculating the FI’s required capital reserves to meet losses above a given level.

49. Loan Portfolio and Concentration Risk

50. Migration Risk
The risk that the quality of a loan or portfolio of loans will decrease (credit risk increase)
If the credit rating of a given industry or group of loans declines then lending in that industry will decrease.

51. Migration matrix
Presents the probability of a loan being upgraded or down graded over a given period of time.
Generally the matrix represents a given industry or region, but could be more widespread.

52. Rating Migration Corporate Debt

53. Using the matrix
If the FI realizes that a larger portion of loans in a category has been downgraded it can chose to reallocate its loans moving some into a higher rating class.

54. Concentration Limits
Limits placed externally on the total amount of credit placed with a given borrower.
The concentration limit is a function of the maximum loss as a percent of total capital and the amount lost in the event of default.

55. Concentration Limit Assume that the Maximum loss is 10%
Loans in the sector on average loose 40% of capital in the event of default

56. Concentration limit con’t
If the firm has $100 million in total capital it would be willing to place 25% of its capital in this sector.
If all $25 Million defaulted, there is a loss rate of 40% (60% gets recovered) or an expected loss of
$25 Million (.4) = $10 Million
which is 10% of total capital

57. Modern Portfolio Theory
Basics of diversification (review)
By increasing the number of assets in the portfolio we can eliminate systematic risk.
The amount of risk that can be eliminated depends upon the correlation of the assets. As long as the assets are not perfectly correlated there is a gain to diversification.
The same idea can be applied to loans.

58. Expected Portfolio Return
The combined return of two assets is simply the weighted average of their returns

59. Variance of Returns
as long as the correlations are less than one (preferably some being negative) the portfolio variance will be reduced.

60. Efficient Frontier
By changing the weights in a portfolio you get different return and risk combinations.
It is often possible to rearrange a portfolio and produce a higher return without changing the risk.
The efficient frontier provides the set of portfolios that produces the highest return at each level of risk.

61. Efficient Frontier
Given four assets, the next slide shows a graph of 76 different portfolios created by changing only the weights in the portfolio.
The vertical axis is the return on the portfolio, the horizontal axis represents the standard deviation of the portfolio.
The efficient frontier is the set of points that provides the highest return for each level of risk.

63. Available combinations
Given the efficient frontier you can increase return for a given level of risk.
You can also decrease risk to find the minimum risk portfolio.

64. Problems with MPT and loan management
Loans and many other assets held by FI’s are often:

65. KMV Portfolio Manger
Since many assets are non traded it is difficult to calculate the inputs in used in modern portfolio theory
Three inputs are needed: return, variance of each asset and correlations (or covariances)

66. KMV portfolio manager Return on Loan AISi = All in Spread
= Spread on the loan + fees
E(Li) = expected loss on loan
EDFi = Expected default frequency
LGDi = Loss given default

67. KMV Portfolio Manger Risk of the loan
ULi=“unexpected” loss on the loan
Assumes defaults are binomially distributed.

68. KMV Portfolio Manager
Correlations are based upon the default risk correlation of the firms assets over time.
The correlations are therefore relatively low ranging from .002 to .15.

69. KMV Portfolio Manager
Given the individual returns, variances, and correlations the portfolio returns can be calculated using the standard portfolio theory.

70. Loan Volume Based Models
Concentration risk can be analyzed based upon data established for large volumes of data for example:
Commercial bank call reports: reports to the Federal Reserve loan allocation among different asset classes. Can be aggregated and used as a benchmark.
Shared National Credits - based on SIC codes. Again can be used for benchmarking

71. Factor based analysis
Based on the systematic loan loss for a given sector
Bi is the systematic loss sensitivity of the ith sector. Where the entire portfolio has a
B =1

72. Regulatory models
General limits are often also set by regulatory agencies.
For example life-health insurers can have at most 3% of their portfolio in a single issuer or security.