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首页> 外文期刊>Journal of Discrete Mathematical Sciences and Cryptography >Influencing factor analysis of credit risk in P2P lending based on interpretative structural modeling
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Influencing factor analysis of credit risk in P2P lending based on interpretative structural modeling

机译:基于解释结构模型的P2P借贷信用风险影响因素分析

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摘要

Managing and preventing the credit risk in Peer-to-Peer lending has become a crucial problem in China’s internet finance market. The influencing factors of the credit risk in P2P lending are identified from three aspects including P2P lending platform, borrowers and environment. The internal relation between these influencing factors is also explored by using the method of Interpretative Structural Modeling. Results show that factors such as the audit mechanism of P2P lending platform could affect the credit risk in P2P lending directly. In addition, borrowers’ moral level, their job stability, and the policy environment will affect the credit risk in P2P lending comprehensively through influencing other factors.
机译:管理和防范点对点贷款的信用风险已成为中国互联网金融市场的关键问题。从P2P借贷平台,借款人和环境三个方面确定了P2P借贷信用风险的影响因素。这些影响因素之间的内在联系也通过解释性结构建模方法进行了探索。结果表明,P2P借贷平台的审计机制等因素可以直接影响P2P借贷的信用风险。此外,借贷者的道德水平,工作稳定性和政策环境将通过影响其他因素来全面影响P2P借贷中的信用风险。

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