Optimization Scheme Of Jingdong White Strip Credit Investigation Mode Based On Federal Learning

In the past few years,there has been a boom in the development of consumer credit products,with more and more participants,especially credit investigation subjects.However,our country’s credit investigation industry is in the stage of improvement,most platforms with credit investigation capability carry out business mainly based on internal data,failing to realize the mode of data sharing and communication to improve the level of the credit investigation industry,so unified and mature standards of the credit investigation industry have not been formed.However,domestic scholars have proposed ways to improve the credit investigation industry from theoretical aspects such as improving legislation,accessing the central bank’s credit reporting,and utilizing technology.Therefore,some credit reporting platforms don’t have concrete and practical steps to solve problems.As a result,the credit reporting industry frequently encounters problems such as incomplete credit data,low data quality,and information leakage.Therefore,it is necessary to carry out specific research on such problems to propose a reference plan to promote the healthy and harmonious development of the credit reporting industry system.In this paper,the research on the credit industry is carried out by using the method of literature review,case analysis,interview,qualitative analysis.Firstly,the model of credit investigation and federal learning theory are summarized from domestic and foreign literatures.Secondly,taking Jingdong white strip as a typical case of credit products to analyze the credit investigation problems and their causes from the perspectives of operation mode,data source and personal credit investigation mode,et al.Finally,in view of the problems of incomplete credit investigation data,low data quality and information leakage,the program based on the perspective of federal learning technology starts with key points such as design and development concept,selection of partners,selection of privacy algorithm and design of federal process,to put forward targeted solutions,hoping to bring a new perspective of development to other credit reporting platforms and our country’s credit reporting industry.