P2P网贷平台跑路风险识别研究

Research on Running Away Risk Recognition of P2P Lending Platform

以100家网贷平台数据为例,通过随机森林算法对平台跑路风险进行分析。结果得出随机森林模型对网贷平台的跑路风险等级分类比较准确。月均成交量、月均投资者人数、平台基本信息和注册资本指标对网贷平台跑路风险等级具有重要影响,而平台逾期率、借款用途和资金存管对网贷平台跑路风险等级的重要性相对较低。因此,可以通过平台月均成交量、月均投资者人数、平台基本信息等指标对平台的风险状况进行初步判断,然后做出相应投资决策。并分别从投资者、监管主体和行业自律组织的角度提出防范网贷平台跑路风险的建议。

Taking 100 network loan platform data as an example,it analyzed the risk of platform running risk by random forest algorithm.The result shows that the stochastic forest model can accurately classify the risk level of the runway of the online loan platform.Monthly average volume of traders,the number of monthly investors,the basic information of the platform and the registered capital have an important impact on the risk level of the platform for the operation of the online loan platform.However,the overdue rates,the purpose of borrowing and the deposit of funds on the risk level of the platform The importance is relatively low.Therefore,the monthly average volume of the platform,the average monthly number of investors,the basic information of the platform and other indicators of the platform to determine the initial risk of the situation.And then making the appropriate investment decisions.From the perspective of investors,regulatory bodies and industry self-regulatory organizations put forward proposals to prevent the risk of network loan platform running way.