基于支持向量机的个人信用评估模型研究

The Model of Personal Credit Risk Assessment On Support Vector Machine

随着我国经济的快速发展,个人信贷业务扩大,给银行带来收益的同时必然存在风险,针对传统个人信用评估方法的不足,鉴于支持向量机具有全局收敛性和良好的推广能力,本文将这种方法应用到信用评估中,利用支持向量机的方法对个人信用进行实证评估,并与K最近邻模型方法进行比较,得出了该方法的可行性和优越性,为银行建立一套完善的评估体系提供依据。

With the development of consumer credit in domestic commercial banks, personal credit is attached to more and more value in our country, which brings the bank both benefits and risks. In the light of dissatisfactions with existing personal credit scoring methods,the support-vector-machine （SVM） , which has many good properties including global convergence and good ability of extension, is put forward and applied to evaluate personal loan application. In this paper, the support vector machine （SVM） is applied to the study of personal credit risk assessment. In contrast with KNN, empirical results show that SVM is effective and more advantageous than other methods,which can help the bank establish a better assessment system.