How to deal with extreme cases for credit risk monitoring: a case study in a credit risk data science company

Abstract

The Global Financial Crisis triggered a severe hold on credit lending due to the financial institutions’ inability to assess credit applicants risk levels properly. Based on U.S. data from Lending Club, we conducted a study to evaluate the consequences of including macroeconomic risk factors in individual credit application observations. Through historical scenario stress testing, we find that this approach results in an increase in performance for credit scoring models developed in a stable economic cycle and applied to a recession. The inclusion of macroeconomic indicators reveals potential for credit institutions to better absorb shocks derived from economic downturns.