Studying product quality by exploring credit card customers behaviour via data mining techniques

Abstract

Recently, the competition has increased among Iranian-banks. This provides customer's satisfaction and quality-optimization. Nowadays, Credit-card is a new and significant product for Iranian-banks. Reports show customer's demand decreased by 21% in using credit-card in 2018. This study is aimed to identify high-quality customers of credit-card and develop the product quality through creating features in accordance with to their needs in order to increase customers' satisfaction. It was conducted on 1598 credit-card holders in two-phases. First, high-quality customers were selected using data-mining tools (K-means/C&RT algorithm); Results show 93 high-quality customers. Second, their data was studied the way of using credit-cards and its features from customers' perspective including how to pay installments, number of facilities documents, etc. Results show that 43% and 57% customers use the credit-card as a loan-card and revolving-credit respectively. Also, most customers of revolving-credit significantly consume allocated-credit in a transaction and start paying their debt in maximum-installments.