Research On P2P Investment Banking Based Big Data

As an important part of internet finance,investment finance has received more and more attention in recent years.The comprehensive analysis and research of the P2P industry development from the perspective of big data will not only help small-scale enterprises to get rid of the difficulties of financing and financing,but also have great significance for changing the way of national financial management.This paper adopts a combination of theoretical analysis and empirical research to conduct a comprehensive analysis and research on P2P investment and wealth management from the perspective of big data.In view of the obvious flaws in the existing research on Internet finance,it conducts a comprehensive analysis of macroeconomic policies and the status quo of Internet development.Explore the internal and external development environment of the company,identify issues that are highlighted in the development of the P2P platform,and propose corresponding solutions;Analyze domestic P2P platforms through empirical research methods,consider the current status of Internet finance,and draw on the excellent P2P in the industry The platform operation mode combines the characteristics of the platform itself to determine a reasonable risk control method and implementation mechanism.This paper proposes a credit rating model for quantitative and qualitative index scores by means of fuzzy mathematics methods and expert scoring methods,and selects a representative domestic 30 well-known online lending platforms at present,and uses the proposed model for credit risk rating.The model is compared with other rating models,and the comparison results verify the scientific and rationality of the model.