A REVIEW OF MACHINE LEARNING IN BANKING RISK MANAGEMENT AND POSSIBLE RESEARCH TOPICS

The 2008 global financial crisis brought to light the fundamental significance of bank risk management (GFC). The primary cause of the economic and financial disaster that ensued after the Great Financial Crisis was banks' utter disdain for risk management in the years preceding 2008. Bank culture and structure have changed as a result of the substantial regulatory measures that have since been put in place to address the flaws and deficiencies that were exposed in the financial services industry. The purpose of this article is to examine the degree to which machine learning has been studied in relation to risk management in the banking industry and to suggest possible directions for future research. It ranks bank-specific risks according to an analysis of bank reports and assesses The domains of risk management in banking where machine learning principles have been used.