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机构地区:[1]湖南大学工商管理学院,湖南长沙410082 [2]湖南省两型社会与生态文明协同创新中心,湖南长沙410082
出 处:《经济经纬》2017年第5期159-164,共6页Economic Survey
基 金:国家自然科学基金项目(71373072);国家自然科学基金项目(71171075);教育部长江学者和创新团队发展计划项目(IRT0916);湖南省两型社会与生态文明协同创新中心资助项目
摘 要:基于某网贷平台2013年11月发放的24期贷款数据,引入新巴塞尔协议的行业风险标准构建RAROC模型,对平台定价模式下的互联网金融网贷风险定价进行分析。实证结果表明,有无违约记录、担保资格审查最近两年查询次数、性别等9个变量对借款人违约行为有显著影响;Logistic风险评估模型能较好地预测网贷违约概率,其线性变换得到的信用评分卡准确性较高;基于新巴塞尔协议的RAROC模型适用于互联网金融网贷,且比网贷平台现行的固定利率定价模式更具灵活性和风险敏感性,有利于提升网贷定价质量。Based on the data of 24 loans released by some internet loan platform in November 2013,this paper introduces industry risk standards of the Basel II Accord into the Risk-Adjusted Return on Capital Model( RAROC) and analyses risk pricing of internet financial loan under platform pricing model. The results show that nine variables,including sex,record of default and inquiries into qualification of guaranty within 2 recent years,have significant impacts on the default behaviors of borrowers. Logistic risk assessment model can predict default probability of internet loans with good accuracy in that the credit score card obtained in this model through linear transformation shows great accuracy. Compared with the fixed interest rate pricing model which is currently widely adopted,the RAROC model based on BaselⅡis proved to be more flexible and risk-sensitive and helpful in improving the pricing of internet loans.
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