Financial Institutions - Chapter 10 Credit Risk of Individual loans

Define credit risk

The risk of financial losses due to counterparty failure to perform their obligations. It can be failure to pay the principal, interest or coupon.

Why is measuring credit risk important for credit-granting FI’s?

It helps financial institutions estimate the chance that borrowers will not repay their loans in full or on-time. This is especially important for banks as more than 50% of their assets are represented by loans.

What are allowances?

The amount of money that the banks set aside for loans that might not be fully repaid, so the loans are shown on the books at what the bank realistically expects to collect.

Is lending beneficial or harmful for a bank?

The potential losses from lending outweigh the potential profits, causing lending to be threatening for the solvency of FI’s.

Briefly explain the two main asymmetric information problems that make loan defaults more common

1. Adverse selection problems: The problem that occurs before the transaction. The lender may attract riskier people that are most eager to borrow money but likely to default.

2. Moral hazard: The problem that occurs after the transaction occurs. The borrower may behave more recklessly because they don’t bear the full cost of the risk

Why is measuring credit risk more challenging than measuring market risk?

• The credit risk distribution is far from normal. The distribution is highly skewed and fat tailed

• Measuring the effect of portfolio credit diversification is more complex. Correlations are not directly observable.

• Time horizon is typically longer, the loan lasts over a couple years so there is limited data

• Importance of knowing the counterparty, to determine the probability of getting paid back.

• Legal issues are important. When there is a bankruptcy, lawyers are always present

How does a bank decide to issue a consumer loan?

The decision as to whether to make a loan is a simple accept/reject decision rather than adjustments to the rate. Sometimes banks implement credit rationing where the lender limits loans or refuses the loan entirely but, If accepted, customers are sorted by loan quantity, depending on the severity of credit risk.

Briefly explain how banks make business credit decisions.

The decision to issue a business loan uses quantity and pricing adjustments.

What are the three models used to measure credit risk?

1. Qualitative models

2. Credit scoring models

3. Newer models

Briefly explain how qualitative models are used to measure credit risk

Banks analyze various aspects of the borrower through the 5 Cs to make a judgement of as to their level of risk.

Briefly explain the 5 C’s of credit risk

1. Character (most important): The applicants lending/borrowing history and willingness to pay.

2. Capital (Structure)/Leverage: The greater the debt, the higher the probability of default. Assess ratios associated with leverage.

3. Cash flow / Capacity: Analyze the expected cash flows and volatility

4. Collateral: Loans supported by specific assets in case of default. These are secured loans

5. Conditions: Business cycle of the economy or level of interest rates

What are the limitations of the 5 C’s model?

This model is subjective, so analysis can vary depending on the loan officer. Additionally, this subjective approach may not be directly correlated with the risk being assessed, and can be contradictory.

How are credit scoring models used to measure credit risk?

They use statistical analysis to determine the relationship or correlations between many variables. They use a quantitative method to assess how these variables affect credit risk.

What variables and approaches do credit scoring models use?

They use historical data on observed borrower characteristics to produce a credit risk score or probability of default measure. Variables depend on borrower type and follow several approaches such as the linear probability model, the probit model and the Altman Z-score, ZETA discriminant model.

What happens if the score or probability of default is a value above a critical bench mark?

The loan applicant is rejected or subjected to increased scrutiny.

Briefly explain the two conditions variables must satisfy in order to be used in credit scoring models?

1. They must be easily observable and inexpensive to obtain

2. The variable must be correlated with the true probability of default that isn’t observed.

List some examples of variables banks collect to determine consumer debt

• Income

• Assets

• Occupation

• Length of employment

• Number of credit cards

• Frequency of credit inquiries

List some examples of variables banks collect to determine corporate debt

• Financial ratios

• Size and type of the business

• The length of time in business

How were linear probability models used in credit scoring?

Using a historical sample of past data and run the model where the probability of default is the sum of beta times each variable.

Why is the linear probability model no longer used in credit scoring?

It’s statistically unsound since the estimate obtained isn’t a probability and can be outside the interval between 0 and 1.

How is the Altman Linear Discriminant Model used to measure credit risk?

The z-score is a weighted average of five variables to determine a consumer’s probability to default. If the Z-score is greater than 2.99 credit risk is low, you are in the “safe” zone. If the z-score is less than 1.80 probability to default is high, you are in the “distress” zone and the interval between 1.80 and 2.99 is the “grey” zone, where additional analysis is necessary.

Briefly explain some limitations to using the Altman Z-score model

• Predictive ability: Can this model really predict new bankruptcies when necessary?

• Applicability/choice of independent variables: A bank should tailor this model depending on their customer and availability of information

• Binary decision: Default or doesn’t default

• Ignores subjective factors

• No centralized database for default

• Based on book value data predominately

• No underlying theoretical model

What are two newer models used for credit risk assessment?

1. Mortality rate derivation

2. The risk adjusted return on capital

Briefly explain the mortality rate derivation approach to credit scoring?

This approach uses past data to analyze default experience. The marginal mortality rate for a certain quality of bonds would be the probability of defaulting after a period of issue. Survival rate equates to 1 minus the marginal mortality rate in each year.

What are limitations to using the mortality rate derivation model?

• Uses historic data

• Is dependent on the time-period you are measuring

• There is a lack of a loan default database of sufficient size

Briefly explain the RAROC model and how it’s used to measure credit risk

This model is a risk adjusted performance measure, and gives an idea of the return adjusted for risk. It does so using the one year net income on a loan divided by the change in the loans market value and incorporates duration to estimate the worst case loss in value of the loan.

According to the RAROC model, when should a loan be approved?

Only if it’s RAROC is higher than a certain benchmark which usually is the cost of funds for the bank. This model is used for deciding whether to go through with the loan and if so, at what interest rate.