For the various violation phenomena existing in the third‐party payment industry，a violation risk early‐warning mechanism based on Random Forest are proposed. A set of index system for violation risk early‐warning is firstly built，then the risk early‐warning mechanism based on random forest algorithm which comes from machine learning methods is proposed. A sample of 271 companies with paid licenses is used to verify the effectiveness of the proposed early warning mechanism for violation risks. By comparing the discrimination rate of Logistic model and Random Forest model，the research finds that both type I error and type II error of Random Forest model are much lower，and Random Forest model has high accuracy of up to 99. 01% when predicting. Finally，through the analysis of important variables，specific application measures and corresponding risk supervision suggestions are put forward.