P2P Online Lending:The Relationship Between Loan Description And Loan Success Rate And Default Rate

As one of the important financial formats of Internet finance,P2 P online lending provides new financing channels for small and medium-sized enterprises and new directions for individual investors in financial management.The problem of information asymmetry in P2 P network lending will lead to that investors' decision-making behavior is largely affected by the information of borrowers.As one of the information of loans,will the loan description affect the success rate of loans? Does the more descriptive the loan,the lower the default rate? The study of this problem has both theoretical and practical significance.In this paper,the influence of loan description information on loan success rate and the relationship between loan description and loan default rate are analyzed by using principal component analysis(pca)and logistic regression model.First,a brief analysis of the network after borrowing process,using the information asymmetry theory analyzes the network of the lending market information asymmetry problem,using cheap talk,anchor theorem deals with highlight in behavioral finance theory analyzes the borrowing description and the relationship between the loan rate,overreact and deficiency and perceived risk theory analyzes the borrowing description and the relationship between the loan default rates,based on the above theory put forward in this paper,the research hypothesis.Secondly,after the variables were constructed,the dimensionality was reduced by principal component analysis(pca),and the relationship between loan description,loan success rate and default rate was analyzed by logistic regression.Finally,according to the empirical results,corresponding policy Suggestions are proposed for borrowers,investors and online lending platforms.The conclusions of this paper are as follows: first,the more detailed the loan description in the loan object,the higher the loan success rate and the lower the default rate;Second,for the description of borrowing funds for express different borrowing description mark,borrowing the success rate is the highest management production class,and personal consumer decorate,borrowing,wedding preparation and other classes,and the last is to buy car,loan default rate is lowest wedding preparation classes and other classes,and then the management production class,finally decorate loan class,individual consumer and purchase a car;Thirdly,for the loan targets with different emotional tendencies revealed in the loan description information,the loan success rate is the highest or the lowest,which are assurance,neutral,supplication and thanks respectively.Loan default rates from low to high are neutral,pleading,guaranteed,thanks.This study provides theoretical support for the policy formulation of P2 P online lending regulators,and has important reference value for how online lending platforms improve the disclosure of loan targets.In addition,the academic community has done a lot of research on the value and influence of the hard information of borrowers in online lending,and the literature about the loan description as the research object in soft information still needs to be supplemented.Therefore,this paper divides the loan description information into three dimensions to conduct novel research content.In addition,the naive bayesian classification method is used to construct the loan description variable in this paper.