Discovering Credit Cardholders’ Behavior by Multiple Criteria Linear Programming

Gang Kou, Yi Peng, Yong Shi (), Morgan Wise and Weixuan Xu

Annals of Operations Research, 2005, vol. 135, issue 1, 274 pages

Abstract: In credit card portfolio management, predicting the cardholder’s spending behavior is a key to reduce the risk of bankruptcy. Given a set of attributes for major aspects of credit cardholders and predefined classes for spending behaviors, this paper proposes a classification model by using multiple criteria linear programming to discover behavior patterns of credit cardholders. It shows a general classification model that can theoretically handle any class-size. Then, it focuses on a typical case where the cardholders’ behaviors are predefined as four classes. A dataset from a major US bank is used to demonstrate the applicability of the proposed method. Copyright Springer Science + Business Media, Inc. 2005

Keywords: data mining; classification; multi-criteria linear programming; credit cardholders’ behavior; SAS algorithms (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10479-005-6245-5

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