Credit Risk Assessment Model for Small, Medium and Micro Enterprises Based on RS-PSO-SVM Integration

摘要

According to the credit characteristics of small, medium and micro enterprises, this paper constructs a risk assessment index system, and introduces rough sets, particle swarm algorithm and support vector machine to carry out research on corporate credit risk classification. First, this paper uses the rough set to reduce the classification indicators and select the key influencing factors of corporate credit risk. Secondly, the PSO algorithm is used to optimize the SVM model parameters, and to assess and classify corporate credit risks, and then solve the problem of nonlinear modeling and multi-collinearity. Finally, empirical evidence shows that the RS-PSO-SVM model has high accuracy and efficiency.