基于社交网络的P2P借贷信用风险缓释机制研究

本文以信息经济学和博弈论为基础,建立信息不对称的理论模型,从事前、事中、事后三个环节分析P2P借贷信用风险成因,讨论社交网络缓解信用风险的机制及其作用条件。研究表明,引入社交网络后,社交网络的事前信息获取机制、事中连带责任机制和事后违约约束机制构成社交网络独特的信用风险缓释机制。连带责任、动态激励、监督强度、违约约束制裁大小、违约约束强度以及对社交信息的挖掘是决定社交网络风险缓释水平的重要因素。当社交网络信息可以实现借款人风险甄别或借款人社交账户可作为充足"虚拟抵押品"时,社交软信息可有效缓解征信不完善导致的事前逆向选择;引入社交朋友关系后,连带责任带来的隐性契约有效缓解缺乏监督机制导致的事中道德风险;社交网络的社会制裁可有效缓解缺乏违约约束导致的事后道德风险,尤其配合停贷威胁的动态激励时其风险缓释作用更为显著。拆解社交网络如何对信用风险产生影响的"理论黑箱",提出了社交网络信用风险缓释机制的理论框架,为如何运用社交网络进行风险控制提供理论支持。

Research on Credit Risk Mitigation Mechanisms of Peer-to-peer Lending Based on Social Network

Risk management is the core issue to determine the sustainable and healthy development of financial innovation. Based on the information economics and game theory, an information asymmetry mathematical model is set up to analyze the acting mechanism and working conditions of social network in mitigating P2P lending's credit risk. It is proved that with the introduction of social network, the credit risk of P2P lending can be mitigated by three mechanisms of social network, which are ex ante information acquisition mechanism, joint liability mechanism and ex post default constraint mechanism. Those constitute unique credit risk mitigation mechanisms of social network, which can effectively relieve adverse selection caused by imperfection of credit system as well as moral hazard caused by lack of effective monitoring mechanism and lack of default constraint mechanism in P2P lending market. Joint liability, dynamic incentive, the strength of supervision, sanctions, constraints of default intensity and the mining of social information are thedetermining factors to the risk mitigation level of social network. The theoretical frameworks are first proposed for credit risk mitigation of social network in P2P lending, including the developed social network theory and credit risk management theory,which provide new scientific evidence and theoretical support for risk control trial with social network in P2P platform. Great theoretical importance is provided to understand and grasp risk mitigation mechanisms of social network, as well as to use social network credit risk management.