Research On Operational Risk Of Financial Institutions Based On Data Mining Technique

Encountering with the gradually complicated financial activities, operational risk management has played a more and more important role in financial control institutions. Operational risk has become an increasingly marked risk factor in global financial institutions. How to identify, measure, monitor and control has become the primary focus of the financial institutions. Considering the complexity of operational risk and the great loss it may cause, how to effectively keep it away becomes a crucial problem to which financial institutions should take active attitude. Through research and analysis, this paper aims to predict the intension of operational risk of financial institutions, and accordingly, to educe correlative rules of the intension of operational risk. Therefore, it plays a role in helping financial institutions analyze operational risk, facilitating administrators establishing appropriate operational risk management strategies, and serves as a theoretical foundation for banks to identify and analyze risk when designing operational risk control of banks as a whole.This paper effectively analyzes the application of data mining techniques in finance, and compares it with data processing meanings in traditional finance. Combined with the characteristics of financial data, it demonstrates the values of data mining techniques in finance.When analyzing operational risk of financial institutions, this paper uses the great advantages of data mining techniques for reference. It makes an original reflection and exploration on data processing and analytical approaches of operational risk, takes comprehensive advantage of data mining techniques, and overcomes the problems caused by the fuzzy definition of operational risk and the diversity of its inducing factors. Together with the establishment of fixed models, this paper assesses the intension of operational risk of financial institutions, and finally reaches the rules of judgment of operational risk.After analyzing the characteristics of operational risk and its measurement, this paper specifically expounds the advantages of data mining technique in financial risk, and expands this technique further on the analysis of operational risk. By establishing fuzzy logic and neutral network, it also analyzes the comprehensive intension of operational risk at different levels, and reaches the bases of identifying operational risk under different circumstances. With the adoption of expert rules and genetic algorithms,...