...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Emerging Markets Finance & Trade >Predicting Prepayment and Default Risks of Unsecured Consumer Loans in Online Lending
【24h】

Predicting Prepayment and Default Risks of Unsecured Consumer Loans in Online Lending

机译：预测在线贷款中无抵押消费贷款的预付款和违约风险

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Online lending provides a means of fast financing for borrowers based on their creditworthiness. However, borrowers may undermine this agreement due to early repayment or default, which are two major concerns for the platform and lenders, since both affect the profitability of a loan. While default risk is frequently focused on credit scoring literature, prepayment has received much less attention, despite a higher prepayment rate being observed in online lending when compared with default. This article uses multivariate logistic regression to predict the probability of both the underlying prepayment and default risks. Real consumer lending data of 140,605 unsecured loans provides evidence that these two events have their own distinct patterns. We consider systemic risk by incorporating macroeconomic factors in modeling and address the influence of economic conditions, which are lessons learnt from the last financial crisis. The out-of-sample validation has shown that both prepayment and default can be accurately predicted. This article highlights the necessity of regulations on prepayment given the fast growing online lending market.
机译：在线贷款提供了一种基于借款人信誉度的快速融资方法。但是，借款人可能由于提前还款或违约而破坏该协议，这是平台和贷方的两个主要问题，因为两者都会影响贷款的获利能力。尽管违约风险经常集中在信用评分文献上，但预付款受到的关注却少得多，尽管在线贷款中的违约风险比违约更高。本文使用多元逻辑回归来预测潜在的预付款项和违约风险的概率。 140,605份无担保贷款的实际消费者贷款数据提供了证据，证明这两个事件具有各自不同的模式。我们通过在模型中纳入宏观经济因素来考虑系统性风险，并解决经济状况的影响，这是从上一次金融危机中汲取的经验教训。样本外验证表明，可以准确预测预付款和拖欠款项。本文强调了鉴于快速增长的在线借贷市场的预付款规定的必要性。

著录项

  • 来源
    《Emerging Markets Finance & Trade》 |2019年第3期|118-132|共15页
  • 作者

    Li Zhiyong; Li Ke; Yao Xiao; Wen Qing;

  • 作者单位

    Southwestern Univ Finance & Econ, Sch Finance, Chengdu, Sichuan, Peoples R China|Southwestern Univ Finance & Econ, Collaborat Innovat Ctr Financial Secur, Chengdu, Sichuan, Peoples R China;

    Southwestern Univ Finance & Econ, Collaborat Innovat Ctr Financial Secur, Chengdu, Sichuan, Peoples R China|Southwestern Univ Finance & Econ, Sch Stat, 555 Liutai Ave, Chengdu 611130, Sichuan, Peoples R China;

    Cent Univ Finance & Econ, Business Sch, Beijing, Peoples R China;

    Southwestern Univ Finance & Econ, Sch Finance, Chengdu, Sichuan, Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    credit; default; online lending; prediction; prepayment; H81; C53; D81;

    机译：信用;违约;在线贷款;预测;预付款;H81;C53;D81;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号