The management committee of Chongqing Liangjiang New Area was informed that the market supervision bureau of Liangjiang New Area has taken "credit + big data" as a grip to establish a supervisory platform of intelligent supervision and precise supervision of market subjects, which has achieved obvious results.

The supervisory platform implements joint disciplinary mechanism through data docking with market subjects of municipal industry and commerce, taxation and other administrative departments, effectively improving the legal awareness of market subjects in the jurisdiction and regulating the market environment, with a total of 26,039 enterprises in the jurisdiction filing annual reports on time in 2017, with a growth rate of 30.6%, of which the annual reporting rate of foreign-funded enterprises exceeded 90%, reaching 91.91%. A total of 3,406 non-compliant companies have been placed on the business exception list. The annual growth rate of market players is more than 25%. Since 2016, 2,329 market entities have been randomly checked; since 2015, 4,157 "zombie enterprises" and "shell enterprises" have been cleaned up in accordance with the law, and 1,259 investment enterprises have been cleaned up and rectified.

It is understood that the market subject supervision platform takes the credit data of market subjects as the core, geospatial library as the basis, and forms a network of market subject supervision information by integrating the existing business system information of industry and commerce, quality supervision and food and drug supervision in Liangjiang New Area, and builds a spatial grid and graded classification supervision platform for market subjects. In accordance with the rules of conduct of market subjects, a corresponding credit classification scheme for market subjects is constructed, dividing market subjects into four categories, namely A, B, C and D, and indicating them in green, yellow, red and black respectively, in order to strengthen the focus of supervision and clarify the supervision center. Through geospatial data mining technology, an intelligent early warning model is constructed to build an early warning model including registration early warning, consumption early warning, regulatory early warning and security early warning, and visualize it on the map to make the regulatory focus clear at a glance.

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