English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62796/95837 (66%)
Visitors : 3639070      Online Users : 549
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/54221


    Title: Discovering cardholders’ payment-patterns based on clustering analysis
    Authors: Shih, Chien-Chou;Chiang, Ding-An;Hu, Yi-Jen;Chen, Chun-Chi
    Contributors: 淡江大學資訊傳播學系;淡江大學資訊工程學系;淡江大學保險學系
    Keywords: Credit card;Data mining;Clustering algorithms
    Date: 2011-09-15
    Issue Date: 2011-07-03 00:42:28 (UTC+8)
    Publisher: Kidlington: Pergamon
    Abstract: This paper sampled approximately 9.3 million entries of data, concerning payments from 300,000 credit card customers over the past two years of Bank A in Taiwan. By applying data mining techniques to decipher customers’ behavior and perform risk analysis, the clustering algorithms divides card users into 9 groups of different levels of contributions and risk profiles, according to their consumption patterns. We generalize a set of clustering rules to identify high risk customer groups in advance. Therefore, the proposed suggestions could tell who was a bad risk and either deny their application or, for those who were already cardholders, start shrinking their available credit and increasing minimum payments to squeeze out as much cash as possible before they defaulted. On the other hand, banks are advised to adjust credit limits in a timely manner for the customer groups whose risks are low and contributions are high, in addition to the provision of value added services, in order to enhance earnings.
    Relation: Expert Systems with Applications 38(10), pp.13284-13290
    DOI: 10.1016/j.eswa.2011.04.148
    Appears in Collections:[Graduate Institute & Department of Insurance Insurance] Journal Article
    [Graduate Institute & Department of Computer Science and Information Engineering] Journal Article
    [Graduate Institute & Department of Information and Communication] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML304View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback