Research on Audit Risk Prediction and Management Based on Machine Learning Algorithm

In order to understand audit risk prediction and management, a research on audit risk prediction and management based on machine learning algorithms has been proposed. This paper analyzes artificial intelligence technology and big data auditing, and proposes and implements an intelligent auditing system based on BP-Adaboost. The system can automatically learn a large amount of historical data by setting different training sample sets, and use test sample sets to verify whether the established model is correct and whether the prediction results are reliable. This not only improves audit efficiency but also reduces audit risks, providing new ideas and methods for related fields.