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.
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Kou, G., Peng, Y., Shi, Y. et al. Discovering Credit Cardholders’ Behavior by Multiple Criteria Linear Programming. Ann Oper Res 135, 261–274 (2005). https://doi.org/10.1007/s10479-005-6245-5
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DOI: https://doi.org/10.1007/s10479-005-6245-5