Prediction of Customer Attrition of Commercial Banks based on SVM Model

Abstract

Currently, Chinese commercial banks are facing triple tremendous pressure, including financial disintermediation, interest rate marketization and Internet finance. Meanwhile, increasing financial consumption demand of customers further intensifies the competition among commercial banks. To increase their profits for continuing operations and enhance the core competitiveness, commercial banks must avoid the loss of customers while acquiring new customers. This paper discusses commercial bank customer churn prediction based on SVM model, and uses random sampling method to improve SVM model, considering the imbalance characteristics of customer data sets. The results show that this method can effectively enhance the prediction accuracy of the selected model.