Design Of Banking Operational Risk Monitoring System Based On Big Data Mining

In recent years,with the opening of the financial market,many kinds of financial innovations have emerged.The scope of financial business has broken the restrictions of traditional regions and networks.The pressure of business development urges financial institutions to avoid risks in time while operating and managing innovations.Data mining technology is an information processing technology that extracts implicit information and knowledge from a large number of practical application data,and uses database,artificial intelligence and mathematical statistics technology to process and analyze data in depth.In the identification of bank operational risk,data mining technology is used to analyze,classify and statistics information related to finance,so as to control financial risk and effectively manage risks.Firstly,this paper reviews the research status of the relationship between big data technology and bank operational risk monitoring,and analyses the types and problems of bank operational risk,as well as the impact of the characteristics,advantages and methods of big data mining technology on business operational risk.On this basis,two points of view are put forward: 1.According to the types of operational risk,the existing risk monitoring model can not effectively find the relationship between data from a large number of data,leading to inaccurate early warning of risk;2.Using the advantages of large data mining technology,it can be applied to complex data of banks,so as to quickly identify risks,and on this basis,establish a wind.Insurance monitoring system.Empirical test results using a sample of agricultural and commercial bank from the second quarter of 2016 to the second quarter of 2017 show that compared with the traditional manual review business mode,through the establishment of large data risk monitoring system,it can effectively,real-time,multi-dimensional operational risk monitoring,and further improve the risk management.Combining the research results of big data mining,the status of operational risk monitoring,the application of big data mining technology,and the risk monitoring system established therefrom,can not only improve the efficiency of banks,reduce labor costs,but also increase the coverage of risks.However,due to the complex environment and huge data,the follow-up suggestion is to introduce artificial intelligence,increase the active learning ability of the system,and retrospect the historical data.By automatically analyzing and recording the new risk situation,we can identify the risk more effectively,and further realize the real-time prevention and control of the operational risk of commercial banks.