1. Risk Management in Banking
Credit Risk
Department of Banking and Financial Management
M.Sc. in Financial Analysis for Executives
Piraeus 2012

2. Contents Introduction Rating Systems Credit Risk: Historical Dates
Using Quant Methods to Assess Credit Risk
Credit Risk Analysis using Bloomberg

3. Credit Risk Definition Example Credit Events:
The potential for loss due to a failure of a borrower to meet its contractual obligation to repay a debt in accordance with the agreed terms
Credit Risk is also referred to as Default Risk
Example
Greece stops making payments to Greek bond holders
A homeowner stops making mortgage payments
A company fails to repay corporate lending
Credit Events:
Bankruptcy
Failure to pay
Loan restructuring
Loan moratorium
Accelerated loan payments

4. Credit Risk versus Market Risk
Potential loss due to changes in market prices
Usually assessed for a day
Credit Risk
Potential loss due to the nonperformance of a financial contract
Usually assessed for a year
Credit risk is generally more important for Banks
Credit Products: Loans, Bonds
Many credit risk drivers relate to market risk drivers
Credit and Market Risk models, to assess risks, both use:
Historical data
Forward looking models
Behavioral models

5. Credit Risk - Drivers Exposure Probability of Default Migration Risks
Size of amount at risk with the counterparty – Direct valuation
Probability of Default
Size of the probability of the event of default – Direct valuation
Migration Risks
Deteriorations or improvements of the credit standing. Needs mark-to-market valuation
Recovery Risk
Take into account guarantees that protects lender from large exposures

6. Credit Risk – Rating Systems
Credit standing of debt issues using coded letters
Relative ranking, not absolute assessment of the level of risk
External Ratings
Third party view on the credit risk of debt
Moody’s, S&P, Fitch
Rates debt issues and not issuers
SWOT Analysis
Strengths
Weaknesses
Opportunities
Threats
Large listed companies and sovereign debt

7. Credit Risk – Rating Systems
Credit standing of debt issues using coded letters
Relative ranking, not absolute assessment of the level of risk
Contrasts with probability of default which quantifies the likelihood of default over a given horizon
External Ratings
Third party view on the credit risk of debt
Moody’s, S&P, Fitch
Rates debt issues and not issuers
SWOT Analysis
Strengths
Weaknesses
Opportunities
Threats
Large listed companies and sovereign debt

8. Credit Risk – Rating Systems
Internal Ratings
Borrowers are usually medium or small businesses/households
External rating not available
Internal Ratings Based approach: strong tendency towards harmonization
Includes:
Borrowers risk
Potential support
Facility risk
Financial attributes for credit standing:
Size
Operating Profitability
Financial Profitability
Financial Structure
Cash Flow
Operating Efficiency
Operating Leverage
Liquidity
Market Value
Volatility of earnings and sales

9. Credit Risk – Historical Data
Yearly Default Rates
Yearly default rates and ratings – Figure 36.1

10. Credit Risk – Historical Data
Cumulative Default Rates
Average Cumulative Default Rates by letter rating from 1 to 20 years ( ) (%) – Figure 36.2

11. Credit Risk – Historical Data
Cumulative Default Rates
Average Cumulative Default Rates by letter rating from 1 to 20 years ( ) (%) – Figure 36.2

12. Credit Risk – Historical Data
Recovery rates by seniority level of debt
Table 36.3

13. Credit Risk – Historical Data
All- corporate rating transition matrix
Table 36.4

14. Credit Risk – Quant Models
Rating models assigns ratings from linking credit status to observable attributes of borrowers
Default risk models are based on similar attributes to derive the default probability
Credit Scoring (discriminate between defaulters and non-defaulters)
Econometric techniques (model default rates of “portfolio segments” or subpopulations of firms by risk class)
Neural Networks (non linear relations)
Scoring Analysis
Discriminant Analysis (Fischer)
The Zeta Score (Altman’s model)