Consumer analytics toward development of cross selling products at retail banking: an approach on big data at Eximbank

Abstract

Based on internal database as big data of the Eximbank, 3,527 active customers with the initial length of service more than 12 months, the method of data mining is concerned, in which the mathematic methods of K-Means of cluster, Tree Decision, and Association Analysis are applied. The findings show that consumers’ characteristics using services at EXIMBANK are various, in which staffs, directors as individual customers occupy a high proportion in total customers. Based on descriptive statistics, there are eight main products, such as VG (Visa Gold), VC (Visa Classis), MG (Master Gold), MS (Master Standard), VP (Visa Platinum), VV (Viva Violet Card), VA (Visa Auto Card), and others are concerned most by the customer, in which VG and VC are the two top cards used. Directors are more interested in VG card, while staffs concern VC card. In addition, using two cards, called the main card and the extra card, is popular. This is a potential chance for the bank to develop cross-selling products, which the product bundle strategies are packed into groups. Based on the method Association Analysis, propobality of using two cards or three cards at the same time of customers are derived. This finding basically supports the bank to address cross-selling products of cards to customers. To do this, recommendations of the strategies of bundle products are suggested in the thesis, together with implementation plans