Application of Data Mining Techniques in Customer Segmentation for Commercial Banks

Abstract

Commercial banks are able to use Data Mining Technology (DMT) to improve their capability to segment customers or gain more thorough insight into their value. By developing DMT research methodologies that incorporate a variety of techniques including clustering methods, classification algorithms and other techniques to analyze multiple dimensions (e.g., customer transaction history and consumer behavior), conclusions can be drawn from the resultant output. Results of the research show that DMT can uncover previously unrecognized patterns of demand among customers, allowing for the design of individualized products and providing banks with a scientific framework for determining the optimal allocation of marketing resources.