Design of Financial Risk Warning System Based on AI Algorithm and Deep Learning

Financial system risk warning is a crucial area of study in the financial sector. The advent of artificial intelligence technology has made machine learning-based risk warning for the financial system a popular research focus. This study examines early warnings for financial system risks using machine learning, with the goal of offering valuable insights and approaches to risk management in the finance industry. It begins by presenting an overview of the importance and relevance of financial system risk warnings, as well as the utilization of machine learning within finance. Traditional statistical methods have limitations, which has led to the development of a particle system through AI and deep learning algorithms in neural network financial distress early warning model. This model offers strong information timeliness and high prediction accuracy rates for test samples. The empirical findings demonstrate that this model provides favorable prediction effects and outperforms traditional models in terms of effectiveness. It is suggested that the particle swarm optimization BP neural network proposed in this study offers a suitable solution for discriminating and predicting enterprise financial distress.