The Research On Improving The Level Of Grassroots Tax Service Informatization Under The Background Of Big Data

Since the 21 st century,with the development of Internet,the Internet has been applied to the work of various government departments,including the public services provided by government departments.The informalization level of tax services of tax authorities has been greatly improved.With the advent of the era of big data,the concept and methods of the work of the tax authorities will continue to undergo new changes.The application of big data concepts,methods and technologies to public services provided by government departments is an inevitable trend nowadays.Big data brings opportunities and challenges to the modernization of tax services in China.In recent years,the "Internet+Taxation" action and the "Running at most once" reform have all been in response to the taxpayer's demand for the improving the level of informationization of grassroots tax services,and have also placed higher demands on grassroots tax authorities.Under the background of big data,how to improve the informationization level of grassroots tax service,improve the efficiency of tax service,and build a comprehensive tax service operation system to fully meet the needs of taxpayers has become new problems.At present,scholars at home and abroad have carried out a series of research and analysis on the improvement of taxation service informationization level and the application of big data in taxation work from different angles,but because of the new big data concept,there is very little research on the combination of big data,tax service,informationization and work practices.This paper learns from the excellent research results at home and abroad.Under the background of big data,based on the new public service theory,tax compliance theory and information asymmetry theory,investigate tax service demand of L district through the method of questionnaire and interview,combined with the results of Zhejiang satisfaction survey.Then summarize the status quo of the taxation service informationization of the L District Taxation Bureau of Wenzhou City,analyze the existing problems and the causes of the problems,propose countermeasures to solve those problems.The research found that the publicity channels of the L District Taxation Bureau are still not rich enough,the ability of personnel team is not strong,and the homogenization of taxation services is serious.The reasons for the above problems include the incompleteness of the taxation service information operation system,the ability of tax personnel team needs to be improved,service concept lags and the level of tax individuality needs to be improved.Starting from the problems existing in the status quo of tax informationization,the article proposes countermeasures from the perspectives of operating system,personnel team and thinking,including improving the information operation of grassroots taxation services by adding big data functions,optimizing the allocation of tax service resources,and improving the information sharing interaction mechanism system;establish a professional service team under the background of big data by establishing a high-quality team,improve the cultivation mechanism,improve the assessment and incentive mechanism;cultivate tax service thinking of big data by paying attention to the value of data,data analysis and application of analysis results.Therefore,the utilization rate of information taxation service means is improved,including broadening the channels for promoting tax service,increasing the scope of use of the electronic tax bureau,simplifying the taxation process,and improving the ability and quality of tax service providers,including the operational and application capabilities of the Golden Tax Phase III,data analysis and application capabilities of the big data,innovative service concepts;improve the scope and extent of big data application in grassroots tax services,including tax resource allocation decisions,personnel recruitment decisions,and personnel assessment mechanisms.