中国网络借贷市场逆向选择、道德风险与信贷配给研究

Online lending (or Peer-to-Peer lending, abbr. P2P) markets contribute to the reform of supply-side and twin engines of “to be entrepreneur, to be innovator”. Adverse selection, moral hazard and credit rationing have become emerging issues which have still not caught the eyes of scholars, after P2P platforms are confined to function as informational intermediaries. This project firstly defines five related concepts, quantitatively processing semi-structured and unstructured data into structured data; then three theoretical models are reconstructed, based on the traditional theories of credit, which is suitable for online lending characteristics. Further the “double two-dimension” mode is applied to measure and analyze adverse selection, moral hazard and credit rationing and their structural features in China’s P2P lending markets; explore the driving mechanisms of adverse selection and moral hazard from borrowers under different states, and of "dual" credit rationing from P2P platforms and investors. Owing to risk characteristics of the P2P lending markets, the traditional theories about “double decreasing” are difficult to apply to efficiency improvement. This project therefore investigates the driving mechanisms of credit misallocation which can provide “three decreasing” space for efficiency. Finally, in order to promote healthily development of Chin’s online lending markets, the risk reduction and efficiency improvement are simulated under two states of information using the simulation techniques. The findings in this project are expected to help not only enrich the research on information asymmetry in P2P lending markets but also solve the realistic issues.

发展网络借贷市场是贯彻供给侧改革和“双创”战略基本要求。在纯信息功能定位后，逆向选择、道德风险与信贷配给已成为突出问题，但还未引起学界重视。本项目从相关五大概念界定开始，通过量化处理将半结构型和非结构型数据转换成结构型数据；通过创新在传统信贷理论基础上重构适合网贷特性的三个新理论模型。以此为基础，采用“双重二维”复合模型测算分析中国网贷市场逆向选择、道德风险和信贷配给状况及结构特征；拟合不同结构状态下借款人逆向选择和道德风险驱动机制、平台和投资人“双重”信贷配给驱动机制。考虑到仅靠传统“两降”理论难以实现效率提升目标，本项目还探索信贷错配驱动机制，为效率提升提供“三降”空间。最后，以配置效率三类指标最优化为目标，构建有约束三目标的非线性规划系统，仿真模拟两类信息状态下不同方式的改进效果，为推进中国网贷市场健康高效发展提供理论依据和建议。本项目不仅弥补了网贷市场理论研究不足，还解决了现实之需。

网络借贷是普惠金融重要组成部分。本项目从信息不对称视角研究了中国网贷市场逆向选择、道德风险与信贷配给：基于网贷特性构建逆向选择、道德风险和信贷配给理论模型；分析中国网贷市场逆向选择、道德风险和信贷配给状况及结构特征；理论解析借款人逆向选择；分析道德风险与驱动机制；仿真测算借款人在不同信贷配给状态时的道德风险；讨论平台经营中的风险与驱动机制；最后测算平台退出市场的道德风险。.两期动态博弈模型发现，信息技术：⑴由于降低经营成本而使得因信贷配给被排斥在外的部分高风险借款人获得信贷但也导致更高道德风险；⑵因降低信息不对称而可通过更精确的风险定价使借款合约更多样化。信息技术在增加信贷可得性同时加剧逆向选择和道德风险。高风险借款人信用状况更可能因高借款成本而恶化从而被配给，信用转好的借款人将进入利率更低市场。样本数据表明，中国网贷市场信息不对称相当严重，存在较高的逆向选择和道德风险。信用等级较差与转为较差的借款人被平台配给。理论模型显示主观贴现率越高、越高估未来收入、借款成本越高的借款人风险越高，而借款人主要为从农村流到城镇的年轻人，主观贴现率高、高估未来收入且对借款成本不敏感，逆向选择严重。道德风险与驱动机制研究发现，中国确实有合适的长尾群体且在稳健平台借款不会产生系统性风险；合适借款人道德风险受年龄、性别、学历、居住地人均可支配收入、信用等级和借款额的显著影响，出借人可根据违约机制优化组合标的获得超额收益。乡城流动借款人违约概率比城市高3%，比农村低1%；流入流出地收入差异与乡城流动借款人违约概率呈U型，违约概率在约3万元时最低；流入流出地收入差异对违约概率影响主要来自流入地收入水平。进一步仿真模拟发现，在只有自然人借款时，平台可通过信贷配给实现稳健运营；但若不断引入法人借款且纵容关联企业融资，则任何平台均难以为继。虽然不同平台出险概率存在差异，但道德风险、公司治理风险、信用管理风险和营运风险越高，平台出险可能性越大。平台道德风险非常严重，在触雷过程中为60%，在恶性退出过程中为74%。至今不少平台仍在利用清零机会加速收割出借人资金。与其他市场杀猪盘和割韭菜高度同源，均为一夜暴富，与劳动价值论和全面依法治国格格不入。.中国不能没有普惠金融市场，它们如同网贷那样处于市场末端，易遭逆向选择和道德风险侵害。本项目成果无论对国内网贷市场浴火重生还是对其他市场功能发挥均具有重要价值。

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