Publication detail

Consistency of Banks’ Internal Probability of Default Estimates: Empirical Evidence from the COVID-19 Crisis

Author(s): Ing. Mgr. Barbora Štěpánková M.A., Ph.D.,
Type: Submissions
Year: 2021
Number: 0
ISSN / ISBN:
Published in: Journal of Banking and Finance (submitted in Jun-21)
Publishing place:
Keywords: Banking, Credit Risk, Model Risk, Bank Regulation, COVID-19
JEL codes: C12, G21, G32
Suggested Citation:
Grants: GACR 20-00178S - The impact of the normalisation of interest rates on risk management PRIMUS/19/HUM/17 2019-2021 Behavioral finance and macroeconomics: New insights for the mainstream
Abstract: The Basel III post-crisis reforms target the application of internal credit risk models for the estimation of risk weighted assets due to concerns about model risk. We use a unique dataset of 4.9 million probability of default estimates covering the January 2016 - June 2020 period sourced from 28 global banks to provide a deep insight into the comparability of model outputs. Our contribution is four-fold. Firstly, we confirm that there is a substantial variance in credit risk estimates. Secondly, we show that the level of variance is dependent on the entity type, industry, and location. Thirdly, we conclude that a considerable part of the variance is systematic, especially for credit risk estimates of funds. Finally, we illustrate the massive impact of the COVID-19 pandemic on the variance. The results highlight areas with relatively larger comparability issues, and they can be used by regulators to design more targeted policies.

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