Credit Risk Management-SPEC:Finance & Financial market

1. Z-score formula - the beginning od this concept and its historical development. 1a. Description of discriminant analysis methodology.

1b. Altman method, as well as other balance sheet-based models are not appropriate for financial companies.

2. Bundesbank's application of discriminant analysis methodology (with 3 factors instead of 5 in Altman's model). 2a. Description of idea how to derive a linear econometric model with those 3 variables with the help of Excel spreadsheet based on data from 10 exemplary companies. 2b. The concept of 3 discrimination zones (safe, gray, distress zones). 2c. Selection of cut-off values based on the bank's “appetite for risk”.

3. Weaknesses of discriminate analysis models.

4. Type I and type II errors - accepting bad credits and rejecting good ones.

5. Other applications of scoring criteria - (a) richness, or service intensity, of customers, and (b) scoring consumer loans with different factors (variables) occurring in the resulting econometric model.

6. Conditional default probability and Bayes’ theorem - examples.

6a. Application of Bayes' theorem in credit decision making.

7. Computation of the number of type I errors - how to minimize them.

8. Construction of a table featuring conditional and unconditional default probabilities based on historical data possessed by a bank.