Introduction

Amnon Levy and Jing Zhang

Credit risk management has changed a great deal since the 1980s, but we are now experiencing profound, rapid evolution in diverse, risk-related areas, at an unrivalled pace. This affects players globally in complex ways, changing how businesses must operate and how they should adapt their risk practices. These changes are one of the most important and timely topics facing credit risk management; they are one area where financial institutions worldwide will spend significant resources in the coming years.

A number of disruptive forces are driving this change. The first relates to rapidly changing technologies, particularly the use of information technology (IT) to increase efficiency. The IT revolution has enabled us to collect and store huge amounts of data for financial risk measurement and management. Advances in machine learning (ML) and artificial intelligence (AI) techniques have allowed data analysis and use in an increasing number of applications. The second force for change, oversight through prudential regulation (eg, Basel III and IV) and reporting standards (International Financial Reporting Standard 9 (IFRS 9) and Current Expected Credit Loss (CECL)), is forcing

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