The increasing perfection of artificial intelligence technology has brought subversive changes to the field of financial risk management. The application of artificial models such as neural networks, support vector machines, and mixed intelligence in financial risk management can improve the speed of data processing, provide deep insight into data analysis, reduce human labour costs, and hence improve the efficiency of financial risk control. Meanwhile, the increasing amount of data and the application of AI also bring new challenges to financial risk management, such as the risk of program error and information security. This paper introduces in detail the application status of three models, including Support Vector Machine, Support Vector Machine, and Large Language Model in risk management Based on this, this paper analyses the advantages of AI applications in promoting and reforming the financial industry. The goal is to provide an in-depth examination of present implementations and their respective benefits, as well as to investigate potential future advances in this sector.