Research on the Application of Artificial Intelligence Technology in Risk Management of Commercial Banks

With the continuous progress and application of artificial intelligence (AI) technology, the use of AI technology in the management of commercial banks has received more and more attention. In this paper, we take commercial bank risk management as the research topic, combine the mainstream technology and examine the specific application. First, it is addressed how commercial banks assess credit risk by using data mining, natural language processing, machine learning (ML), and deep learning (DL) in commercial banks’ credit risk assessment is discussed. Then, the risk control of commercial banks is discussed from three aspects: data mining and analysis, risk control model building, and risk control decision-making. After that, the advantages of AI in commercial banks, such as dealing with nonlinear problems, excellent data acquisition, and real-time monitoring of transactions, are discussed. And the limitations of AI in commercial banks, such as data discrimination and interpretability are discussed. It turns out that risk management involves, AI technology can effectively improve credit risk assessment results and can effectively prevent fraud risks. The value of this dissertation is to afford a reference for the research and practice of AI in areas related to risk management applications.