Abstract
We describe the risk management challenges faced by financial institutions. The very nature of the banking business requires that financial firms become experts at risk assessment in order to manage their own inventories of risk, obtained during day-to-day business transactions with their customers and third-party vendors. Banks are exposed to interest rate risk, currency risk, liquidity risk, credit risk and operational risk. The first step in a risk management program is to understand the nature of the risk and to accurately measure their risk exposure. One of the useful risk measurement tools is the Value at Risk (VaR) model. In addition, with recent advances in financial technology and the explosive pace of data collection, more complex analyses using alternative data, artificial intelligence (AI) and machine learning (ML) have penetrated all areas of finance, including bank risk measurement and management. Partnership between banks and fintech firms has created tremendous benefits through product innovations (better, faster, and cheaper) and enhanced efficiency, although new types of risk have emerged. Approaches to bank risk measurement and management continue to evolve as we move into a new financial and banking landscape.
