Research On The Quality Management Of Financial Statistics Data Of Grassroots Central Bank

Financial statistics is an important part of the national statistical system.It is not only an important tool to support monetary policy decisions,maintain financial stability,and effectively conduct financial supervision,but also an important means to monitor the operation of various economic sectors and markets.As a barometer of economic operation,financial statistics reflect not only the operation of the financial system,but also the operation of the economic system and even the entire social system.In recent years,financial statistics have been paid more and more attention by the society,and the public has put forward higher requirements for data quality.As the competent authority for financial statistics nationwide,the quality of the People’s Bank of China’s statistical data directly affects the statistical authority and credibility of the People’s Bank of China.With the continuous promotion of comprehensive statistics in the financial industry,the coverage of financial statistics is becoming wider,the granularity of data is becoming smaller,the data structure is becoming more complex,and the connotation and extension of financial statistics are expanding,which makes the quality management of statistical data face unprecedented challenges.Branches at all levels of the People’s Bank of China,as producers of source data,collect,review and integrate basic financial data,which are summarized level by level to form national statistical data.Therefore,the financial statistics work of the grassroots central bank is the "cornerstone of the statistical tower".Whether the "cornerstone" is firm will directly affect the quality and efficiency of the overall work of financial statistics of the People’s Bank of China.How the grassroots central banks adapt to the new situation of statistical work,update the concept of data management,improve the means of data control,ensure the quality of statistical data,and enhance the credibility of statistics deserves in-depth research.Based on the theory of responsible government and the theory of total quality management,the article adopts the method of combining interview and case analysis,and closely combines with the actual work of financial statistics management of central branch C of the People’s Bank of China.And concludes that the source data quality in data quality management is not high,the job satisfaction of statisticians is low,the work efficiency of financial statistics is not high,the published data content cannot fully meet the needs of users,and the enforcement atmosphere of financial statistics is not strong.According to the analysis of the existing problems,the main reasons are the lagging revision of financial statistics laws and regulations,insufficient statistical infrastructure guarantee,weak statistical team construction,insufficient statistical data production process management,and incomplete data quality supervision and management system.The innovation of this article is based on the "grassroots",the research object is specific,and combined with the author’s work experience,to avoid wide,large,empty and extensive.Based on the experience of foreign statistical data quality management,combined with the theory of responsible government and the theory of comprehensive data quality management,from the perspective of the statistical institutional environment,personnel security,technical support,statistical process,and supervision system,this paper puts forward countermeasures such as optimizing the statistical management system of the grassroots central bank,strengthening the construction of financial statistics team,improving the infrastructure of data management,improving the process management of statistical data production flow,and improving the data quality supervision and management system.The financial industry in City C is relatively developed.The problems encountered by the central branch of the People’s Bank of China in the management of financial statistics are representative,and the countermeasures proposed are highly targeted and operational.It has certain reference value for the grass-roots central banks in other regions to conduct statistical data quality management.