Research On Uni-power Group's Mode Of Credit Investigation System For Middle And Small Enterprises Under The Backdrop Of Big Data

The biggest barrier for financing of middle and small enterprises is limited financing channels and ways.Recently,the financing methods for middle and small enterprises can be divided into internal and external financing.Internal financing mainly includes capital from the owner(or partner,shareholder)and capital borrowed from relatives and friends and personal investment,etc.The external financing mainly refers to capital gained from bank credit,stocks and bond,etc.In recent years,credit investigation system plays an important role in building the system and technology of credible society.The traditional credit system based on personal integrity has transferred to system of evaluating the willingness and ability of the fiduciary to perform the obligations in the agreement.Particularly in recent years,with the rise of emerging technologies such as Internet and big data,people's behavior in social and economic life is recorded by network data so the credit investigation system can evaluate the qualifications of fiduciary based on tradition in a broader way and more information of the fiduciary can be recorded and quantified.By processing,extracting and analyzing the data in specific business scenario,the credit side can get more relevant information and evaluate the credit accurately.Compared with traditional credit investigation system,the new system is more scenario-based,accurate,real-time and efficient so it is an important supplement for the traditional system.Recently,China is vigorously developing Internet+ and big data strategy,building creditable society and promoting inclusive finance innovation.Under this backdrop,this essay analyzes innovation and development of credit investigation of big data enterprises and researches on the innovative case of enterprise credit investigation system with the core of “SMEES” conducted by Uni-Power Group in big data society.The basic theory of “SMEES” is 9 business elements.The system refers to the display form of F10 of the listed company,covers 9 modules of the enterprise,111 indicators and 198 data items.It also makes segmented and complicated expression systematic model targeting at different industries,scales and business modes.The system has comprehensive data,integrated supporting materials,dynamic real-time follow-up and includes non-financial indicators so it solves the problem of unclear information of small and middle enterprises and dissymmetry of the information between banks and enterprises.Therefore,the system is well applied in business practices of companies.Based on the practical cases and experience of Zest Finance,a foreign big data credit investigation company,the author offers advice which adapts to the business scenario.Under the backdrop of recent sluggish entity economy,the author recommends that the credit investigation system of Uni-Power Group could focus on monitoring the risk of enterprises which have credit extension authorized by banks and other financial institutions,collect varied risk data,focus on data mining and data analysis,apply machine learning ability and keep information association as the direction to explore the mode and direction of innovation and development of big data credit investigation.