Bank Deposit Customer Forecast Based On Decision Tree

In recent years,with the development of the Internet,some Internet financial products also come,which certainly can bring about huge impact to the traditional banking.There are a large number of customer data in bank,but the use of the data is not enough,the increase of the data does not bring the growth of the information and produce huge benefits.This article focuses on how to use data mining techniques,and improve the success rate of the bank deposit and under the premise of considering the imbalanced data,dealing with the customer data,and according to the classification results are targeted to subscribe to the recommended to reduce the cost of bank,finally achieving the purpose of increasing the profit of the bank.In data mining analysis,this paper adopts the unbalanced algorithm to deal with data and uses the decision tree algorithm,to select and analyze the characteristic of customer types,and find out the influence on bank deposit for larger characteristics.Making customer classification according to the characteristics of the corresponding performance,to recommend for potential clients,and reduce the cost of bank by recommending blindly,and increase the success rate effectively.