CLASSIFICATION OF BANK DEPOSITOR USING ID3 AND NAIVE BAYESIAN CLASSIFIERS

Abstract

Nowadays, banks are financial institutions whose activities are to collect funds from the public in the form of deposits (saving deposit and time deposit). Deposits are an alternative for customers because the interest offered on deposits is higher than regular savings. So, this system is proposed as the bank depositor classification system by using data mining (DM) methods. Among many DM methods, this system uses the ID3 and Naive Bayesian classifiers to classify bank customer’s data. This system predicts which customer will subscribe to a long-term deposit proposed by a bank. Moreover, this system analyses the sensitivity, specificity and accuracy of ID3 and Naive Bayesian classifiers. This system can help the bank for identifying customers who will potentially open a time deposit so that it can be used to assist the performance and operations of the bank.