Risk Management Analysis of Modern Commercial Banks Using Behavioral Finance Theory and Artificial Neural Networks

Abstract

With the increasing trend of economic globalization, China’s pace of promoting interest rate marketization is gradually accelerating, and financial market volatility is increasing day by day. Credit risk is at an all-time high for commercial banks. The most significant risk that banks face is credit risk. The methods and technologies of commercial bank risk management have improved with the accelerating process of financial globalization, but the rationality of risk managers who implement daily management is limited and will be influenced by emotion and will. As a result, they will be unable to implement completely unbiased risk management, i.e., they will not be able to apply risk management objectives to daily risk management in an optimal manner. The importance and measurement complexity of commercial bank credit risk is growing in tandem with the financial market’s increasing complexity. The traditional credit risk assessment model is no longer adequate to meet the requirements of today’s financial risk management system. The research into the credit risk assessment model is both theoretically and practically significant.