摘要
网络借贷作为一种新型互联网金融模式,提升了金融资源使用效率,缓解了小企业融资难的困局。构建合理的网络借贷信用评价指标体系,从而对网络借贷的潜在风险及时甄别与预防,对互联网金融健康持续发展意义重大。本文根据K-S检验与距离相关分析相结合,筛选对借款客户违约状态甄别能力强的指标,建立了网络借贷信用评价指标体系,通过P2P网络借贷(peer to peer lending,个人对个人借贷)平台LendingClub交易数据进行实证研究,结果表明:不仅借款金额、借款利率等借款标的特征对借贷者违约具有显著相关性,借款者年龄等个人特征、借款者年收入等财务特征以及借款者违约次数等信用特征均对借贷者违约风险产生显著影响。投资者在出借资金时,往往青睐于已婚、年龄适中、具有一定工作经历、历史违约次数较少的借款人。因此,风险监管部门应构建网络借贷违约风险评估模型,对P2P平台进行风险监测,同时建立关键信息共享机制,融合多源数据,明确审查范围,实现P2P网络借贷行业健康有序发展。
As a new model of Internet finance,online lending improves the efficiency of financial resources utilization and alleviates the difficulty of small enterprises in financing.It is of great significance for the healthy and sustainable development of Internet finance to construct a reasonable credit evaluation index system of online lending,so as to screen and prevent the potential risks of online lending in time.Based on the combination of K‐S test and distance correlation analysis,this paper selects the indicators with strong ability to screen the default status of borrowing customers,and establishes the credit evaluation index system of online lending The empirical research on lending Club transaction data shows that not only the loan amount,loan interest rate and other characteristics of the loan object have significant correlation with the borrower’s default,but also the personal characteristics such as the borrower’s age,the financial characteristics such as the borrower’s annual income,and the number of borrowers’default have a significant impact on the borrower’s default risk.When lending funds,investors tend to favor the borrowers who are married,of moderate age,have a certain work experience,and have less historical defaults.Therefore,the risk supervision department should build a default risk assessment model of online lending,monitor the risk of P2P platform,establish a key information sharing mechanism,integrate multi-source data,and clarify the scope of review,so as to realize the healthy and orderly development of P2P network lending industry.
作者
段翀
Duan Chong(School of Economics,Inner Mongolia University of Finance and Economics,Hohhot 010070,China)
出处
《技术经济》
CSSCI
北大核心
2020年第5期35-47,59,共14页
Journal of Technology Economics
基金
国家自然科学基金“基于违约金字塔原理的小企业贷款定价模型”(71171031)
国家自然科学基金青年科学基金“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”(71201018)
内蒙古自然科学基金面上项目“基于基准利率风险补偿的小企业贷款定价模型”(2017MS0709)。
关键词
网络借贷
信用评价
违约显著区分
K-S检验
距离相关系数
network lending
credit evaluation
significant distinction of default
K⁃S test
rank correlation coefficient