Statistically distinguishable rating scales

Mikhail Pomazanov

Journal of Risk Model Validation

Abstract: This paper proposes a method of designing a statistically distinguishable rating scale that is not excessive in relation to the existing observation statistics. This allows for more stable validation with a fixed maximum number of violations of the Wald criterion compared with the excess scales usually used by banks. The increased validation robustness will reduce the calibration probability of default, providing savings in the capital requirements under the advanced internal ratings-based approach. Theoretical justifications of the effect are presented, along with numerical calculations for three rating scales: two based on publicly available data from rating agencies, and a third on proprietary data from a bank. The proposed method is most relevant for the corporate segment of the loan portfolio.

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