Research on Financial Risk Control Model and Algorithm Based on Machine Learning under the Background of Rural Revitalization Strategy

The strategy of rural revitalization is of great significance to the reconstruction of rural economic growth, in which rural industries, represented by the integration and development of rural industries, have sprung up. The purpose of this paper is to use machine learning (ML) technology to build an effective risk control model, so as to help Internet finance enterprises better control the loan risk. Sample data of Internet financial platform borrowers are extracted from multiple dimensions, and then the data are further processed, and the data used to build the model is extracted by feature engineering. Combined with the Gradient Boosting Decision Tree (GBDT) algorithm in ML algorithm, the comprehensive evaluation is carried out by using the basic information of bank customers, flow records, user detection information and user detection scale. The performance of the wind control model is further improved by ML, which provides guidance and reference for the performance improvement of the model.