Research On P2P Online Loan Investor Information Discernment Capability Based On Reptile Data

During the two sessions in 2018,Premier Li Keqiang proposed to strengthen the overall coordination of financial supervision and improve the supervision of Internet finance.The government work report has focused on the development of internet finance for five consecutive years.Since 2014,it has been gradually deepening from “promoting the healthy development of internet finance” to promoting the development of normative development of internet finance and vigilance risks,and deepening the current state of sound supervision,reflecting the country’s policy level.Supported the development of internet finance,raised the development of internet finance to a strategic height,continuously strengthened cognition of internet finance,and improved its supervision system.As one of the main modes of Internet finance,P2 P online loan has been growing vigorously in China in recent years.According to the information disclosed by the official website of the Lending Network,as of February 2018,the total number of online lending platforms in China reached 6054.In February 2018,the monthly transaction volume of China’s P2 P network lending was as high as 169.044 billion yuan,and the accumulated historical turnover was 661.1144 billion yuan.Yuan,this shows that the folk “grassroots” micro-lending model has shown a rapid expansion and development trend in China’s financial market.Although China’s online loan platform is set by the borrower itself,but the country sets an upper limit on interest rates,the market is not completely effective,and the phenomenon of information asymmetry still exists.Therefore,the online loan interest rate cannot fully reflect the needs of fund demanders.Probability of default.Investors in the online loan market are at a disadvantage in information.If investors have the ability to identify information,it means that investors in the online loan market have a sense of rational balance,which in a certain sense can guarantee that P2 P network loans can be used properly.The role of information mediation can also improve the allocation efficiency of financial resources,and can avoid the default risk of borrowers from the source.Therefore,it is necessary to study the capability of investor information recognition in China’s P2 P lending market.This article uses Python software to crawl the 396,993 transaction records of the Renren website through the crawler technology.Starting from the reality basis of the development of the online loan platform in China,this paper details the information asymmetry theory and rational investment related to investor information identification capabilities.Based on the inductive deduction method,and based on the inductive deduction method,we reviewed and categorized the literature on the operating model of online lending platforms,information disclosure by borrowers,and investor behavior analysis,based on the typification of China’s P2 P network loans.By constructing a theoretical model and a mechanism analysis,we will explain the theoretical information on the ability of online loan market investors to identify information.Step by step,step by step,conduct empirical research from the three aspects of default risk and interest rate correlation,investor participation and default risk,and full-scale state influence factors,in order to verify investment from the quantitative perspective of data and measurement models.Does the person have the ability to identify information? The following conclusions are drawn: First,there is a significant positive correlation between the interest rate and the risk of default.Second,default risk has a significant impact on the number of investors participating.The information asymmetry between lenders and lenders in the online loan industry is more apparent than that of traditional commercial banks and other lending industries.Investors may have risk aversion when selecting investment targets for borrowing,so the risk is higher.Investors The amount of lending to be invested will be relatively reduced,and the number of investors participating in the full mark will increase.Third,the target information has a significant effect on the full-scale status,and investors have information identification capabilities.For orders with relatively high interest rates,the higher the risk of default,the less likely that lenders will prefer such targets.In addition to the interest rate level,other variables also play a role in the full-scale status.Order information such as the amount of the contract,repayment deadline,and borrower’s age,education,marital status,history of borrowings,historical overdue times,and whether or not the car is required have significant impact on whether the target is full or not.From the point of view of the full standard,investors will select orders with lower risk levels by identifying useful information other than interest rates and interest rates.That is to say,investors in the online loan industry are capable of information identification and risk judgment.Finally,according to the research conclusions,we will steadily promote the marketization of interest rates in the online lending market,gradually improve the soundness of the financial credit system,and comprehensively strengthen the policy recommendations on the popularization of online loan security education.