Determining Retention and Profitability of Bank Customers Using Extended Decision Tree and Forest Regression

In this paper, effective factors on retention and profitability of customers a state owned bank was studied using random forests and regression forests methods. The data was collected form Bank Sepah database. The statistical population consists of 169 corporations holding different types of deposit accounts and utilized one of the different types of services such as sending and receiving payment orders, letters of credit (LC) and foreign exchange facilities during the research period (1389-1391), simultaneously.
In this paper, the accuracy of the results of random forests method is compared with the results of logistic regression and bagging methods using area under the Receiver Operating Characteristic (ROC) curve. Furthermore, the results of regression forests method was compared to those of linear regression by calculating Mean Absolute Percentage Error (MAPE). Then, we tried to determine the importance of effective independent variables on dependent ones, i.e. next purchase, activity defection, profit drop and profit continuity using random forests and regression forests.
The results show that in the case of offering currency facilities to the customers active in the production fields leading to opening LCs and receiving more payment orders will increase the probability of customer retention. In addition, an increase in the amount of foreign exchange facilities and payment orders offered by banks due to the rate of return of foreign exchange facilities, banking fees, income resulting from issued warranties and selling currencies plays an important role in the profitability of customers.