运筹与管理2016，Vol.25Issue(6)：181-189,9.DOI:10.12005/orms.2016.0218
基于不均衡数据的小企业信用风险评价
Credit Rating of S mall Enterprises Based on Unbalanced Data
摘要
Abstract
Small enterprises credit risk evaluation is an issue of banks’risk management,and is also related to the economic and social stability.For small enterprises loans,the default samples are far less than the non-default samples.Also,the impact on banks of default customers’misjudgment is much larger than the impact on banks of non-default customers’misjudgment.In this paper,this research will use the unbalanced support vector machine to weight the evaluation index and construct the credit scoring model for small enterprises.Firstly,the index weights are determined,according to the influence of the specific evaluation index on default and the influ-ence of the index data on default.The greater the influence on default is,the bigger the weight will be.Secondly, using the correct rate of default samples and F-score as the evaluation model test standard,it will change the phenomenon that the overall accuracy is high,but the default samples’accuracy is not high,which is caused by the unbalanced data.Finally,an empirical study of a Chinese national commercial bank’s of 3111 small enter-prises loan observations is given and the result shows that industry climate index,capital immobilized ratio,net cash levels,Engel’s coefficient,operating profit are the key index of credit rating model of small enterprises.关键词
信用风险评价/小企业贷款/不均衡支持向量机Key words
credit rating evaluation/small enterprises’loans/unbalanced support vector machines分类
管理科学引用本文复制引用
程砚秋..基于不均衡数据的小企业信用风险评价[J].运筹与管理,2016,25(6):181-189,9.基金项目
国家自然科学基金青年项目“基于不均衡支持向量机的小企业信用风险评价理论与模型”（项目批准号71201018）；国家自然科学基金“基于违约风险金字塔原理的小企业贷款定价模型” （）
