Credit Risk Modeling in the Age of Machine Learning

64 Pages Posted: 18 Nov 2021 Last revised: 14 Jul 2023

See all articles by Martin Thomas Hibbeln

Martin Thomas Hibbeln

University of Duisburg-Essen - Mercator School of Management

Raphael M. Kopp

University of Duisburg-Essen - Mercator School of Management

Noah Urban

University of Duisburg-Essen - Mercator School of Management

Date Written: July 13, 2023

Abstract

Based on the world’s largest loss database of corporate defaults, we perform a comparative analysis of machine learning (ML) methods in credit risk modeling across the globe. We find substantial benefits of ML methods for different credit risk parameters, even though we use a uniform modeling framework for the ML methods, which potentially facilitates a massive reduction in operational resources required for model development and validation. We analyze the economic drivers of the credit risk models using explainable ML methods and find large variations in feature importance suggested by different ML methods. We propose to implement a nonlinear forecast ensemble, which not only boosts predictive performance but also produces more stable forecasts and economic sensitivities, thereby mitigating model uncertainty. Our results provide guidance for financial institutions, regulatory authorities, and academics.

Keywords: risk management, credit risk modeling, machine learning, forecasting

JEL Classification: G17, G21

Suggested Citation

Hibbeln, Martin Thomas and Kopp, Raphael M. and Urban, Noah, Credit Risk Modeling in the Age of Machine Learning (July 13, 2023). Available at SSRN: https://ssrn.com/abstract=3913710 or http://dx.doi.org/10.2139/ssrn.3913710

Martin Thomas Hibbeln (Contact Author)

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany
+49 203 379-2830 (Phone)

Raphael M. Kopp

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany

Noah Urban

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstrasse 65
Duisburg, Nordrhein-Westfalen 47057
Germany

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