 Consistency of banks' internal probability of default estimates: Empirical evidence from the COVID-19 crisisBarbora Stepankova and Petr Teply Journal of Banking & Finance, 2023, vol. 154, issue C Abstract: The Basel III post-crisis reforms target the application of internal credit risk models for the estimation of the risk weighted assets of banks due to concerns about model risk. We use a unique dataset of 4.9 million probability of default (PD) 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 PD 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 PD variance. The results highlight areas with relatively larger comparability issues, and they can be used by regulators to design more targeted policies. Keywords: Banking; Credit risk; Probability of default; Bank regulation; COVID-19 (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:154:y:2023:i:c:s037842662300167x DOI: 10.1016/j.jbankfin.2023.106969 Access Statistics for this article Journal of Banking & Finance is currently edited by Ike Mathur More articles in Journal of Banking & Finance from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.