Credit Risk Modeling in the Presence of Central Bank and Government Intervention

19 Pages Posted: 29 Oct 2021

See all articles by Bernd Engelmann

Bernd Engelmann

Ho Chi Minh City Open University

Date Written: September 18, 2021

Abstract

Since the outbreak of Covid-19 and the central bank and government interventions that followed, new challenges in credit modeling have emerged. Relations between credit risk and macroeconomic drivers that have been fairly stable over decades have broken down. An example is the unemployment rate which has been widely used in predicting default rates in retail loan segments. Since mid-2020 this no longer works because of government interventions like monthly payments to citizens which allows them to service their debt despite suffering income loss due to unemployment or business closures. This results in substantially lower default rates than predicted by credit models. In this article, using data published by the US Federal Reserve Bank in Q1 2021, a framework is suggested that quantifies the effect of central bank and government interventions and shows how to include intervention scenarios into credit models improving the accuracy of their short-term predictions and allowing analysts to evaluate long-term scenarios. Furthermore, potential side-effects of intervention like increased inflation are quantified.

Keywords: Credit Risk, Default Probability, Covid-19, Basel II, IFRS 9, Stress Testing

JEL Classification: G21

Suggested Citation

Engelmann, Bernd, Credit Risk Modeling in the Presence of Central Bank and Government Intervention (September 18, 2021). Available at SSRN: https://ssrn.com/abstract=3926171 or http://dx.doi.org/10.2139/ssrn.3926171

Bernd Engelmann (Contact Author)

Ho Chi Minh City Open University ( email )

Ho Chi Minh City
Vietnam

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
87
Abstract Views
565
rank
391,248
PlumX Metrics