Increase of banks' credit risks forecasting power by the usage of the set of alternative models

Abstract

The paper is aimed at comparing the divergence of existing credit risk models and creating a synergic model with superior forecasting power based on a rating model and probability of default model of Russian banks. The paper demonstrates that rating models, if applied alone, tend to overestimate an instability of a bank, whereas probability of default models give underestimated results. As a result of the assigning of optimal weights and monotonic transformations to these models, the new synergic model of banks' credit risks with higher forecasting power (predicted 44% of precise estimates) was obtained.