Data mining techniques are used in order to develop a credit risk management system for commercial banks. Firstly, the concepts related to data mining and data warehouse technology were introduced, and the existing credit management situation was analyzed. Subsequently, a credit risk management model was designed and implemented based on data mining, taking into account the actual characteristics of China's commercial banking industry. On this basis, attributes were selected before the classification, which not only improved the overall performance of the classifier but also reduced the cost of data acquisition, enabling commercial banks to improve the efficiency of their credit work.