Research On The Government Supervision Of Personal Credit In The Era Of Big Data

With the development of information network technology and the advent of big data era,the traditional government supervision mode needs to change.In the process of building a service-oriented government,the government uses information network technology and collects credit information for credit supervision,which can improve the administrative supervision efficiency of the government and promote the gradual improvement of social credit system and social governance.China’s government regulation of personal credit is still in exploration and practice.Due to the lack of detailed laws and regulations on credit big data at the national level,there are many problems in the collection,sharing and application of personal credit information,and there are many problems to be solved in the regulation of personal credit.Therefore,it is the key of government supervision of personal credit to improve the practical problems.Firstly,the thesis defines the meaning of personal credit and government supervision of personal credit in the era of big data.In the era of big data,the characteristics of government supervision of personal credit are elaborated: the diversification of credit data sources,the intelligence of credit data processing and the wide application of credit data.Secondly,it analyzes the practical obstacles in the application of big data in the government supervision of personal credit,including the lack of clear standards for the collection and update of personal credit information,the nonstandard sharing mode of personal credit information,and the narrow application scenarios of personal credit information.In order to solve this problem,this thesis proposes to establish a unified personal credit information platform,standardize the sharing and exchange mode of personal credit information,and expand the application scenarios of personal credit information.Thirdly,the thesis analyzes the risk and regulation of algorithmic decision-making in government regulation of personal credit.This thesis discusses the four risks of algorithm decision-making: data distortion,result discrimination,unclear responsibility allocation and insufficient credit repair.Three aspects of regulatory measures are proposed: first,to improve the use of personal credit algorithm decision-making,to better play the role of algorithm decision-making;Secondly,clarify the responsibility distribution of individual credit algorithm decision-making,and protect the rights of citizens in the algorithm decision-making;Third,improve the personal credit repair mechanism to protect the basic rights of credit subject.Finally,the thesis analyzes the defects of the government supervision and relief mechanism of personal credit from two aspects.In view of the specific problems existing in the internal administrative relief and external judicial relief of the subject of personal credit information,it proposes that the relevant rights of the subject of personal credit information should be actively protected.At the same time,according to the problems existing in the system of objection,administrative reconsideration,administrative litigation and administrative compensation,this paper puts forward the improvement of relief mechanism.