drake drake university fin 129 credit risk fin 129 financial institutions management

DrakeDRAKE UNIVERSITY

Fin 129

Credit Risk

Fin 129Financial Institutions

Management

DrakeDrake University

Fin 129Assessment of Credit Risk

FI manager must be able to:Price Loan correctly based upon riskevaluate possibility of default and make sure total risk limits are not violated


Fin 129Credit Quality

Recent concern over the quality of credit:Rapid growth in loans (over 10% a year in the late 1990’sCommercial Real Estate LoansLow-quality auto loansCredit cards

Impact on charge offsSince 1991, the ratio of nonperfoming loans (90 days past due) has actually increased while growth has increased.


Fin 129

Commercial and Industrial Loans

Syndicated Loan -- provided by a group of FI’s instead of an individual lender -- spreads riskSecured Loan - backed by specific assetsUnsecured Loan - only a general claim on assetsSpot Loan --borrower takes entire amount at one point in time in contrast to a loan commitmentCommercial paper -- short term unsecured borrowing by firms


Fin 129Real Estate Loans

Mainly Mortgage Loans creates prepayment risk and default risk.

Adjustable Rate Mortgagesinterest rate is adjusted periodically.


Fin 129Consumer Loans

Credit Card loansRevolving Credit- Open line of credit where the borrower can borrow and repay at willUsury Ceilings -- maximum rate that an FI can charge on consumer and mortgage debt


Fin 129Credit Analysis

Essentially default risk analysisinvestigating 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)


Fin 129

Evaluating Credit Risk the 5 c’s +1

Character -- Capacity -- Capital -- Conditions – Collateral -- Cash --

Which of the characteristics is the most important?


Fin 129Evaluating 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 repaidWorks to the disadvantage of small and first time lenders

CapacityDoes the representative have the legal ability to commit the firms resources



CapitalBorrowers wealth position and can it withstand changes in economic conditionsLook at simple ratio analysis, Debt equity ratio Volatility of earnings - more volatility implies higher probability of default

(Cash)Liquidity of capital



ConditionsMarket Specific Factors, common to all firmsCurrent phase of business cycle and relation to business of firm

CollateralWhat assets can be pledged to secure the loan?Are claims on assets senior to other claims?


Fin 129

Stages of Credit EvaluationHistorical Perspective

Overview of management & operationsBusiness and industry outlook report i.e. competitors, suppliers (conditions)Background info (character)

Common size financial ratio analysiscompare 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


Fin 129Stages of Credit Evaluation

First three provide historical perspective -- then look at futureProjections of borrowers financial condition

Pro forma Financial Statements Attempt to provide an objective outlook at the future prospectsRun sensitivity and Scenario Analysis on the projections


Fin 129

Credit Execution and Administration

Loan CovenantsSpecific requirements either party must

adhere toAffirmative requires borrower to take certain actions (Maintain liquidity position)Negative -- restricts the borrower from certain actions (acquiring more debt)

Credit ReviewReview outstanding loans and monitor problems loans


Fin 129


Default ScenariosWhat actions (or inactions) would constitute defaultWho is responsible for collection costs, attorney fees etc…What actions the are the lender legally allowed to take.


Fin 129


Documentation Collateral needs to be “perfected” -- FI wants to have senior claims

Position LimitsThe maximum amount of allowable credit to a single borrower

Risk RatingFI can grade (rank) individual loans and counter parties (we explain how soon)


Fin 129

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.


Fin 129

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.


Fin 129Credit Scoring Models

Linear Probability and Logit ModelsUses 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)


Fin 129

Linear Prob. and Logit models

For the given set of variables the following regression can be estimated:

variableeobserveabl theX

lejth variab theof importance estiamted theB

default nofor 0 default,for 1Z

eXZ

ij

j

i

ij

n

1jji


Fin 129

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.


Fin 129

Linear Prob and Logit Models

Strengths

Weaknesses

Use of logit solves this

ii Zof valuermedly transfologistical the)F(Z1

1)(

iZi eZF


Fin 129

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.


Fin 129A 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.


Fin 129Fico 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.

Source www.Fico .com


Fin 129Distribution of Fico Scores*

1%

5%

7%

11%

16%

20%

29%

11%

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

<500

500-549

550-599

600-649

650-699

700-749

750-799

>800

Score

Percentage

source www.fico.com


Fin 129Fico Score Comparison

Score Rate SpreadAdditional

Cost

720-850 5.783

700-719 5.903 .125 $4,308

675-699 6.446 .663 $23,139

620-674 7.596 1.813 $64,870

560-619 8.531 2.74 $100,138

500-559 9.289 3.506 $129,139

$150,000 30 year fixed rate mortgage national averages


Fin 129Components of Credit Score (Fico)

Payment History

35%

Amounts Owed30%

Length of Credit History

15%

New Credit10%

Types of Credit

Used 10%


Fin 129Payment History

Payment Info on specific types of accountsPublic Records (bankruptcy, suits, wage adjustments, past due items, etc.)Severity of past delinquenciesTime since delinquency or poor public rec.Number of Number of


Fin 129Amounts Owed

Total amount owed on accountsAmount owed on specific accountsLack of a specific type of balanceProportion ofProportion of


Fin 129Length of Credit History

Time since account openedTime since account opened, by type of accountTime since account activity


Fin 129New Credit

Number of recently opened accounts and proportion of accounts recently opened by typeNumber of recent credit inquiriesTime since recent account openings by typeTime since credit inquiryRe-establishment of positive credit history following past problems


Fin 129Type of credit used

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


Fin 129Note

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.


Fin 129Not in your credit score

Race, age, religion, nationality, sex, marital status (Regulation B)Salary, Occupation, title, employer, date employed, employment historyLocationRates charged on outstanding creditChild/family support obligations and rental agreements.


Fin 129Average Credit Statistics

Number of Obligations: 11, 7 credit cards, 4 installment loansPast 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%<$1000 54% < 10% > $10,000Total (less mortgages) 54% < $5,000, 30% > $10,000


Fin 129Average 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 creditLength of Credit History: average 12 years1 in 5 have histories over 20 years, 1 in 20 shorter than 2 yearsInquires: one a year average, less than 7% have more than 4 inquiries in past year.


Fin 129

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 changesIgnores some relationships such as borrower lender relationships.No centralized database of business loans to provide measure of market risk.


Fin 129Newer Models of Credit Risk

Term Structure ApproachesMortality Rate ApproachesRAROC modelsOption ModelsCredit MetricsCredit Risk +


Fin 129Term 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.



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



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

9722.08.1

05.1

)1(

)1(

k

ip



If the loan is perceived to have a 1-.9722 = .0277 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 represent the proportion of the loan that is recoverable

(1-p)(1+k) +p(1+k) =(1+i)This can also be extended to the case of multi period debt instruments



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.


Fin 129Marginal Mortality Rate

The marginal mortality rate of the loan is the probability of the of the loan defaulting in a given year of issue

1-iin maturities and funds sinking calls, defaults,for adjusted

issue of iyear in goutstandin classloan of valuetotal

issue of iyear in defaulting classloan of valuetotaliMMR


Fin 129RAROC Models

Risk Adjusted Return on Capital ModelsIncome should be adjusted for fees and interest spread


Fin 129RAROC

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

R))R/(1( L D - L

premiumcredit in

change maximum expected

loan

of size

loan the

ofduration

riskat

capital

L


Fin 129

CreditMetrics and Credit Risk +

Credit Metrics 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 RiskCalculating the FI’s required capital reserves to meet losses above a given level.

DrakeDRAKE UNIVERSITY

Fin 129

Loan Portfolio and Concentration Risk


Fin 129Migration 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.


Fin 129Migration 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.


Fin 129

Rating Migration Corporate Debt

Aaa Aa A Baa Ba Bb

C or D

total

Aaa 91.9 7.38 0.72 0 0 0 0 100

Aa 1.13 91.26 7.09 0.31 0.21 0 0 100

A 0.10 2.56 91.2 5.33 0.61 0.2 0 100

Baa 0.00 0.21 .36 87.94 5.46 0.82 0.21 100


Fin 129Using 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.


Fin 129Concentration 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.


Fin 129Concentration Limit

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

rate loss

1

capital ofpercent

a as loss Maximum

Limit

ionConcentrat


Fin 129Concentration 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 Millionwhich is 10% of total capital


Fin 129Modern 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.


Fin 129Expected Portfolio Return

The combined return of two assets is simply the weighted average of their returns

n

1ttt ))(Return(Weight


Fin 129Variance of Returns

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

n

i

n

i

n

ji

jjiijjiiip XXX

1 1 1

222


Fin 129Efficient 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.


Fin 129Efficient 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.


Fin 129

0

1

2

3

4

5

6

7

0 2 4 6 8 10


Fin 129Available 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.


Fin 129

Problems with MPT and loan management

Loans and many other assets held by FI’s are often:


Fin 129KMV Portfolio Manger

Since many assets are non traded it is difficult to calculate the inputs in used in modern portfolio theoryThree inputs are needed: return, variance of each asset and correlations (or covariances)


Fin 129KMV portfolio manager

Return on Loan

AISi = All in Spread

= Spread on the loan + feesE(Li) = expected loss on loan

EDFi = Expected default frequency

LGDi = Loss given default

][)( iiiiii LGDEDFAISLEAISR


Fin 129KMV Portfolio Manger

Risk of the loan

ULi=“unexpected” loss on the loan

Assumes defaults are binomially distributed.

iiiiDiii LGDEDFEDFLGDUL )1(


Fin 129KMV 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.


Fin 129KMV Portfolio Manager

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


Fin 129Loan 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


Fin 129Factor 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

Loans Total

LossLoan Total

sectorith in the Loans

sectorith in the losses Sectorali


Fin 129Regulatory 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.

drake drake university fin 129 credit risk fin 129 financial institutions management

Documents

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credit risk fin

credit risk inherent

credit analysis

quality of credit

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prepayment risk

default risk analysis