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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.

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