Drake DRAKE UNIVERSITY Fin 129 Credit Risk Fin 129 Financial Institutions Management.
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Transcript of Drake DRAKE UNIVERSITY Fin 129 Credit Risk Fin 129 Financial Institutions Management.
DrakeDRAKE UNIVERSITY
Fin 129
Credit Risk
Fin 129Financial Institutions
Management
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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
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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.
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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
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Fin 129Real Estate Loans
Mainly Mortgage Loans creates prepayment risk and default risk.
Adjustable Rate Mortgagesinterest rate is adjusted periodically.
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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
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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)
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Fin 129
Evaluating Credit Risk the 5 c’s +1
Character -- Capacity -- Capital -- Conditions – Collateral -- Cash --
Which of the characteristics is the most important?
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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
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Fin 129Evaluating the 5 c’s
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
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Fin 129Evaluating the 5 c’s
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?
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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
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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
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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
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Fin 129
Credit Execution and Administration
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.
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Fin 129
Credit Execution and Administration
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)
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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.
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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.
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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)
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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
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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.
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Fin 129
Linear Prob and Logit Models
Strengths
Weaknesses
Use of logit solves this
ii Zof valuermedly transfologistical the)F(Z1
1)(
iZi eZF
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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.
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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.
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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
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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
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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
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Fin 129Components of Credit Score (Fico)
Payment History
35%
Amounts Owed30%
Length of Credit History
15%
New Credit10%
Types of Credit
Used 10%
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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
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Fin 129Amounts Owed
Total amount owed on accountsAmount owed on specific accountsLack of a specific type of balanceProportion ofProportion of
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Fin 129Length of Credit History
Time since account openedTime since account opened, by type of accountTime since account activity
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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
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Fin 129Type of credit used
Number of (presence, prevalence, and recent info on) various types of accounts (credit cards, installment loans, mortgage etc)
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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.
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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.
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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
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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.
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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.
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Fin 129Newer Models of Credit Risk
Term Structure ApproachesMortality Rate ApproachesRAROC modelsOption ModelsCredit MetricsCredit Risk +
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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.
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Fin 129Term 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
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Fin 129Term structure approaches
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
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Fin 129Term structure approaches
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
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Fin 129Term 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.
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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
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Fin 129RAROC Models
Risk Adjusted Return on Capital ModelsIncome should be adjusted for fees and interest spread
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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
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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.
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Fin 129
Loan Portfolio and Concentration Risk
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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.
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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.
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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
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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.
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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.
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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
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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
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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.
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Fin 129Expected Portfolio Return
The combined return of two assets is simply the weighted average of their returns
n
1ttt ))(Return(Weight
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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
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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.
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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.
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Fin 129
0
1
2
3
4
5
6
7
0 2 4 6 8 10
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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.
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Fin 129
Problems with MPT and loan management
Loans and many other assets held by FI’s are often:
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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)
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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
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Fin 129KMV Portfolio Manger
Risk of the loan
ULi=“unexpected” loss on the loan
Assumes defaults are binomially distributed.
iiiiDiii LGDEDFEDFLGDUL )1(
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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.
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Fin 129KMV Portfolio Manager
Given the individual returns, variances, and correlations the portfolio returns can be calculated using the standard portfolio theory.
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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
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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
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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.