The study on risk rating model of commercial bank credit based on SVM

Abstract

According to the basic theories of Logit regression analysis and support vector machine (SVM), this article involves improved binary classification combination algorithm to increase the accuracy. In addition, using financial data of listed companies to test this improved model, it shows a better way of classification. When applying this model, there are some innovations: 1. Choose optimized composite indicator as a variable through principal component analysis and get more information; 2. Introduce Logit parameter model to the quadratic to increase prediction accuracy; 3. Put forward a combination of improved Logit model with SVM to increase prediction accuracy. This paper is supported by the Industrial Safety Engineering (239010522).