The Design Of Distributed Credit Risk Control System For Internet Finance Based On Deep Learning

At present,with the rapid development of mobile payment in China,many of cash transactions are gradually replaced by different financial institutions.With data connectivity and integration and other factors for the rapid development of Internet finance provides the conditions,how to efficiently and accurately carry out credit risk control has become one of the main factors that affect the rapid and healthy development of major financial institutions and Internet platforms.In addition.fraud management,brush and other bad behavior also affect the normal development of credit risk assessment.The essence of finance lies in the risk control mobile payment promotion and popularization for the Internet financial data environment but also on the Internet financial risk control made a new scene and new problems.Therefore,this paper analyzes and studies the feasibility and practicability of the application of the deep-learning algorithm in the credit risk control and evaluation of the Internet environment and carries out the experimental verification.This paper begins with the background of credit risk control,the related theoretical methods and the introduction of new problems and challenges under Internet finance.Based on the current understanding of the main methods of credit control and assessment(including traditional methods based on business experience,statistical methods,methods based on financial derivatives and methods based on machine learning)the details of the current Several deep-learning algorithms and frameworks have been developed in other areas to apply good results.Combined with the mainstream of the current Internet financial platform,the distributed technology environment,the design of the system some of the distributed application technology key points were described and analyzed.Based on the theory and technology,this paper presents a design model of credit risk control prototype system with DBN model as the core,and elaborates and designs each function module.In this paper,based on the actual user data of an Internet financial platform,this paper realizes the actual comparison between the designed system and the traditional rule-based risk control system,so as to verify that the deep-learning technology has high feasibility and practicality in the field of credit risk control.