Design And Implementation Of Banking Operational Risk Monitoring System Based On Business Intelligence

The traditional method of risk monitoring of bank operation is to prevent the risk trading in the banking business by manually reviewing the data in the huge database.This kind of monitoring method have the defects of low monitoring efficiency,poor monitoring quality and high labor cost,which severely limits the bank's business development and affect business efficiency.In recent years,with the rapid development of the internet,bank trading business is in the rapid growth.However,the characteristics of the business banking industry determine that all the transactions must ensure zero error rate and high security.Thus,establish an intelligent risk monitoring system to ensure the accuracy of the transaction and the safety of the bank funds,are important to banks and have practical application prospect.In this thesis,a risk monitoring system is build based on business intelligence owing to the current defects of banking operation system.This thesis build a risk monitoring system based on analyzes the current situation of banking risk monitoring at domestic and abroad,and points out the development trend of banking transaction and the shortcomings of risk monitoring system.The main work of this thesis is as follows:First,this thesis analyzes the demand of bank risk system,and designs the whole frame risk monitoring system,which includes the overall architecture design,functional design and ETL design.Second,this paper analyzes the advantages of binary tree,and establishes a binary tree multi-classification support vector machine(BTMC-SVM)model based on the binary tree structure.The test data is used to train the model to obtain the model parameters,so as to classify the huge transaction data in the bank database and distinguish the risk transaction data.Third,on the basis of the system design,the functional modules are designed in detail,including system architecture design,business monitoring and intelligent capture,database design.The bank operational risk monitoring system build in this paper can meet the risk monitoring of bank requirements.Moreover,a commercial bank operation data is provided for the test the designed binary tree multi-classification support vector machine algorithm.The test results show that the risk monitoring model proposed in this thesis has good precision and can extensive reduce labor force of business bank.This thesis designs the banking monitoring system based on business intelligence overcomes the shortcomings of the traditional manual monitoring effectively,which plays an important role in promoting the banking business.