Use Of "Big Data" In Recognizing Risk Customs

In recent years,Internet companies enter the financial sector relying on "big data".The traditional financial industry had to change the original management mode,explore the transformation and upgrading way,and gradually change to intensive and meticulous management.The traditional financial industry has a large number of credit data and customer information.It has the basis of "big data",and the application of "big data" is one of the trends of traditional financial restructuring.Although the large-scale use of "big data" in banks is not mature,some banks have made tentative application of "big data" technology to solve the problem and enhance the efficiency of service from the individual business specific products.This article focuses on the "big data" application of the identification in risk customers.This is an attempt of the "big data" application in company business.This paper first introduced the "big data" concept and "big data" application in the banks,described the significance of "big data" application in the banks,and then discussed the general process of "big data" application in banks.On this basis,the internal information of a bank as a "big data" sources was used to analyze some financial indicators for identifying risk customers.The importance of these indicators was quantitated through the acquisition of basic data,the key index selection,model establishment,application of data verification.This paper applied the concept of "big data" to the risk customers,expanded the scope of "big data" applications in banks,and used multiple regression model to find the key indicators of risk identification in specific industries.It will make banks more scientific in credit risk management,and keep the leading position of the banks in the financial industry.At the same time,we hope this research can provide a basis for the further research of "big data" application,and contribute to the development of "big data".