Research On Credit Supervision Of Tianjin Real Estate Brokers Based On Big Dataapplication

In the process of rapid development of China’s real estate brokerage institutions,dishonesty behaviors such as false publicity,deceiving consumers,and failing to perform contracts as required have occurred,which not only caused great economic losses to the real estate traders,but also disrupted the real estate market and tarnished the overall image of the real estate brokerage industry.Standardizing the real estate market through credit supervision is an innovation of government departments in supervision.With the rapid development and wide application of big data technology,big data has begun to be used in the credit supervision of real estate brokerage institutions,which reduces the workload of government regulators and improves work efficiency.However,as big data has just emerged,its application from technology development to practice is not yet mature,so big data has encountered great difficulties in the application of credit supervision in real estate brokerage institutions.This paper takes credit supervision of real estate brokerage institutions in Tianjin as the research object,uses in-depth interviews and questionnaires to understand the current situation of credit supervision of real estate brokerage institutions in Tianjin and the application of big data,and finds out the difficulties faced by real estate government regulators in applying big data.Then,using the theory of government regulation,the theory of information asymmetry,the theory of collaborative governance,combined with my years of work experience,try to put forward corresponding solutions to promote the better application of big data in the credit supervision of real estate brokerage institutions.The research found that the credit supervision department of Tianjin real estate brokerage institutions faced a big dilemma in the process of applying big data.First of all,there are many problems in the credit supervision basis of Tianjin Real Estate Brokerage Agency Credit Management Measures,which makes the data obtained at the source not accurate enough to reflect the real situation of the brokerage agency’s dishonesty;Secondly,the information transmission speed is slow and cannot be shared,which is not suitable for the characteristics of fast transmission speed and sharing of big data;Thirdly,the construction of the credit publicity platform is lagging behind,and the credit publicity module of the real estate brokerage agency has not been established,resulting in the platform being unable to generate big data for analysis and utilization;Fourth,the government regulatory authorities and brokerage institutions did not attach importance to credit supervision,which resulted in the failure to implement the Tianjin Real Estate Brokerage Credit Management Measures and the failure to collect and analyze big data;Fifth,the construction of talent team and organizational structure is insufficient,and there is a lack of excellent big data professionals such as IT departments and data engineers who apply big data.The staff of the regulatory department have little understanding of the application mode of big data;Sixth,big data has not been fully applied.In response to these problems,corresponding solutions are proposed:further improve the Credit Management Measures of Tianjin Real Estate Brokerage Institutions,establish and improve the credit publicity platform,improve the importance of government supervision departments and real estate brokerage institutions on credit supervision and big data application,and strengthen the construction of big data talent team.The research in this paper will help Tianjin real estate government regulators better apply big data in the process of credit supervision,and also provide reference for other cities in China in the application of real estate credit supervision in big data.