P2P信贷利率影响因素研究——以Lending Club平台为例

Research on the influencing factors of P2P credit interest rates——By Lending Club platform as an example

美国最大的P2P平台Lending Club中只有FICO信用评分高于660的申请者才有资格借款,且仅10%的成功率。其表明在借款时借款人属性对平台划定的其信用等级起显著影响。为分析这种影响,本文研究借款人各项属性对利率的影响,以此来探索P2P平台运营和风控机制。研究表明:该平台通过衡量借款人属性来划定借款利率时,贷款金额、总循环额度等因素影响较大。不同利率层次下对借款人的属性存在偏好,高信用等级意味着更为严格的属性考察。本文的研究结果可为借款人用来实现自我贷款利率预测,也为建立新型的贷款利率定价模式与风险控制体系提供了理论支持。

Applicants are eligible to the largest US P2P Lending Club platform only FICO credit score higher than 660 borrowers, and only a 10% success rate. Which indicates that the borrower attributes platform delineated its credit rating from a significant impact. To analyze this effect, the impact of the properties of the borrower’s interest rate, in order to explore the P2P platform operators and risk control mechanism. Studies have shown that： When the platform by measuring the borrower to designate property loan interest rate, such as loan amount, the total amount of circulating factors are greater influences. Different levels of interest rates for borrowers preference exists properties, high credit rating means the more rigorous study of the properties. Results of this study can be used to accomplish self lending rate prediction,but also provides theoretical supports for the establishment of new lending rate pricing models and risk control system.