Service overview

Credit risks assessment

Figure 2. Example of a crisis’ effect on the credit system - extra losses from main risks in a negative macroeconomic situation.

Let us suppose that a certain bank’s main line of business is loans to individuals. Risks of customers defaulting on their obligations partially or completely will always be present. In an effort to minimize losses the bank studies sales channel quality, analysts create score cards e.g. with data from credit history agencies, and borrowers with high scores, likely to return the loan, get approved. The bank also systematically controls and improves collection efficiency. Effective mathematical models for modeling and assessing risks are used, more are being created. Total risk level and capital adequacy are also evaluated by the bank specialists. Their computation according to Basel committee standards requires that unforeseen losses from loan, market and operational risks be taken into account. Several times a year the Risk Management department will run stress tests.

BSC offers automated loan risk computation, expected loss (EL) and unexpected loss (UL) estimates, scenario-based loss evaluation. Credit risks assessment also varies with planning horizon, credit portfolio structure and many other factors. This is why a systematic approach is called for – just what RRAS provides.



The author presents the methods for studying credit portfolio behavior in the Modeling and Stress-Testing Credit Portfolio Behavior are partly based on so-called “dual time dynamics” method. This work suggests using dual time dynamics not for decomposing scalar values but for decomposing matrices. The author considers a credit portfolio as a process described by a first-order heterogeneous Markov chain. Starting from this premise, the author uses vintage analysis and the theorem of strong convergence of modified fixed-point algorithms to arrive at transition matrix decomposition. This method makes highly accurate forecasts of credit portfolios possible. Reserves can be estimated with excellent precision and relevant values for stress-testing obtained.

In his later article The Theory and practice of Retail Credit the author considers some successful practical applications of his methods described in the article “Credit portfolios behavior modelling and stress-test”.