In order to understand the environmental trend of network finance and the impact of network finance on traditional ommercial banks, after analyzing the transaction risks of network finance, this study learns from the advanced models of credit risk measurement and early warning at home and abroad and the latest artificial intelligence technology, combining them with China’s national conditions, so as to establish a credit risk measurement system suitable for commercial banks. In this study, the research is carried out from the perspectives of theory and practice, technology and business, and the credit risk warning system, measurement model and implementation tools are comprehensively sorted out, then the basic theories and core ideas are studied. In accordance with the concept of big data mining, this study proposes a financial crisis early warning model based on artificial intelligence system. Based on the empirical analysis of the main causes of the rapid decline in the asset quality of China’s joint-stock​ commercial banks, and based on the characteristics of big data mining in the information explosion era, it is pointed out that the artificial intelligence is a powerful tool to improve the ability of credit risk measurement. It can be confirmed that the development of network finance has brought different impacts on the business, business model, and business philosophy of banks.