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http://dx.doi.org/10.9728/dcs.2018.19.1.85

A Customer Segmentation Scheme Base on Big Data in a Bank  

Chang, Min-Suk (Division of Information Security Graduate School of Information Security, Korea University)
Kim, Hyoung Joong (Division of Information Security Graduate School of Information Security, Korea University)
Publication Information
Journal of Digital Contents Society / v.19, no.1, 2018 , pp. 85-91 More about this Journal
Abstract
Most banks use only demographic information such as gender, age, occupation and address to segment customers, but they do not reflect financial behavior patterns of customers. In this study, we aim to solve the problems by using various big data in a bank and to develop customer segmentation method which can be widely used in many banks in the future. In this paper, we propose an approach of segmenting clustering blocks with bottom-up method. This method has an advantage that it can accurately reflect various financial needs of customers based on various transaction patterns, channel contact patterns, and existing demographic information. Based on this, we will develop various marketing models such as product recommendation, financial need rating calculation, and customer churn-out prediction based on this, and we will adapt this models for the marketing strategy of NH Bank.
Keywords
Customer Segmentation; Big data; Clustering; Self-Organizing Map; CRM;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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