Research on intelligent risk control of banks based on BP neural network

Credit business income is the main source of income for banks, and effective prevention of credit risk is an important task for banks' operation and management. The application of various intelligent technologies in the financial field can provide strong technical support to the management of credit risk. How to use big data technology and artificial intelligence algorithms to improve risk control is an important research topic for commercial banks. To address the above issues, this paper studies the theories and technology applications related to artificial intelligence, risk management, and neural networks In this paper, by constructing a BP neural network model, determining evaluation indicators, and using model simulation and validation, risk assessment is performed on bank customer credit risk indicator data, and the validation reflects that the model has a better ability and high accuracy for customer risk prediction, which provides a reasonable determination of customer credit indicators and reduces It provides data basis for reasonable determination of customer credit indicators and reduction of bad debt losses of banks.