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Bank-sourced transition matrixes: are banks' internal credit risk estimates Markovian?

Publication at Faculty of Social Sciences |
2022

Abstract

This study explores banks' internal credit risk estimates and the associated bank-sourced transition matrixes. We empirically test the widely used Markovian property and time homogeneity assumptions at an unprecedented scale.

Our unique data set consists of internal probability of default estimates from 12 global banks that employ an advanced internal ratings-based approach, covering monthly observations on 20 000 corporates over the period 2015-18. The results indicate that internal credit risk estimates do not satisfy the two assumptions, showing evidence of both path dependency and time heterogeneity even within the period of economic expansion.

Banks tend to revert their rating actions, which contradicts previous findings based on data from credit rating agencies. This has significant practical implications through bank-sourced credit transition matrixes, which are becoming increasingly important as regulators begin to use more detailed credit risk data sets (eg, analytical credit data sets by the European Central Bank) with potential applications in stress testing.