The Research On Decision Tree Algorithm In The Bank Risk Monitor

These years, the scandal of stealing the fund the within the banking happened continuously. For the reason of the automation of the banking business and the complicate of the system, the system is more dependent to IT technique; the risk monitor is more complicate. How to monitor the risk in time, how to control the risk in certain scale, we need to look for a swift, effective method to approach the risk monitor.This dissertation firstly discusses the definition of the classification of data mining, analysis the application of data mining in financial area in and abroad. On the base of above, using related data, analysis the risk monitor business of banking, makes a study of decision tree algorithm of data mining and applies the decision tree algorithm to the model building process of banking risk monitor. Secondly, the dissertation sets up Banking Risk Monitor System. The system will cancel the risk in the initial stage by means of risk promotion, early warning and monitor, so as to weaken the extent of destruction to bank. The system uses the framework of J2EE (JSF + Spring + Hibernate), sets up a extendable application plan with component technique, the system is easy to establish, high extendable, loose coupling. Finally, the experiment result declares that the system performs well, and meets the requirement to a great extent.