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

Posted: 2 May 2022

See all articles by Bernd Engelmann

Bernd Engelmann

Ho Chi Minh City Open University

Date Written: November 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 had 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, such as monthly payments to citizens, which allow borrowers to service their debt despite suffering income loss due to unemployment or business closures. This results in substantially lower default rates than those predicted by credit models. Using data published by the US Federal Reserve Bank in 2021 Q3, this paper suggests a framework that quantifies the effect of central bank and government interventions and shows how to include intervention scenarios in credit models, improving the accuracy of their short-term predictions and allowing analysts to evaluate long-term scenarios. In addition, potential side effects of intervention, such as increased inflation, are quantified.

Keywords: credit risk,default probability,Covid-19,Basel II,International Financial Reporting Standard 9 (IFRS 9),stress testing

Suggested Citation

Engelmann, Bernd, Modeling Credit Risk in the Presence of Central Bank and Government Intervention (November 18, 2021). Journal of Risk Model Validation, Vol. 16, No. 1, 2022, Available at SSRN: https://ssrn.com/abstract=4095716

Bernd Engelmann (Contact Author)

Ho Chi Minh City Open University ( email )

Ho Chi Minh City
Vietnam

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