Financial Credit Risk Control Strategy Based on Weighted Random Forest Algorithm

Abstract

In order to improve the effectiveness of financial credit risk control, a financial credit risk control strategy based on weighted random forest algorithm is proposed. The weighted random forest algorithm is used to classify the financial credit risk data, construct the evaluation index system, and use the analytic hierarchy process to evaluate the financial credit risk level. The targeted risk control strategies are taken according to different risk assessment results. We compared the proposed method with two other methods, and the experimental results show that the proposed method has higher classification accuracy of financial credit data and the risk assessment threshold is basically consistent with the actual results.