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作 者:都红雯[1] 郑尚洲 DU Hong-wen;ZHENG Shang-zhou(School of Economics,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)
机构地区:[1]杭州电子科技大学经济学院,浙江杭州310018
出 处:《杭州电子科技大学学报(社会科学版)》2020年第5期23-29,共7页Journal of Hangzhou Dianzi University:Social Sciences
基 金:国家社会科学基金重点项目(17AGL008)。
摘 要:文章以“人人贷”平台2018年6月1日至2019年9月30日交易数据为样本,运用Python编写网络爬虫程序摘取31614个有效交易样本,采用Logistics回归模型及OLS回归模型分别就借款描述的文本长度对违约率、借款利率的影响关系进行探究分析。实证发现,借款描述的文本长度对违约率、借款利率均呈正向影响关系,文本长度越长,借款利率越高,越容易发生违约风险。对此,建议P2P网贷平台结合借款描述来建立更加完善的信用评价机制,降低信用风险,以促进P2P行业持续稳定发展。Based on the transaction data of Renrendai platform from June 1,2018 to September 30,2019,this paper uses Python to compile a web crawler program to extract 31614 effective transaction samples,and uses logistics regression model and OLS regression model to explore the relationship between the text length of loan description and the default rate and loan interest rate.Empirical results show that the length of the loan description has a positive impact on the default rate and the loan rate.The longer the text length is,the higher the loan interest rate is,and the more prone to default risk.In this regard,it is suggested that P2P online lending platform should establish a more perfect credit evaluation mechanism combined with loan description to reduce its credit risk,so as to promote the sustainable and stable development of P2P industry.
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