Classifications of credit cardholder behavior by using multiple criteria non-linear programming
He, J; Shi, Y; Xu, WX
2004
Source PublicationDATA MINING AND KNOWLEDGE MANAGEMENT
ISSN0302-9743
Volume3327Issue:1Pages:10,154-163
AbstractBehavior analysis of credit cardholders is one of the main research topics in credit card portfolio management. Usually, the cardholder's behavior, especially bankruptcy, is measured by a score of aggregate attributes that describe cardholder's spending history. In the real-life practice, statistics and neural networks are the major players to calculate such a score system for prediction. Recently, various multiple criteria linear programming based classification methods have been explored for analyzing credit cardholders' behavior. This paper proposes a multiple criteria non-linear programming (MCNP) approach to discovering the bankruptcy patterns of credit cardholders. A real-life credit database from a major US bank is used for empirical study on MCNP classification. Finally, the comparison of MCNP and other known classification methods is conducted to verify the validation of MCNP method.
Subject AreaComputer Science ; Information Systems ; Artificial Intelligence ; Computer Science
Indexed BySCI
Language英语
WOS IDWOS:000227493600017
Citation statistics
Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.casisd.cn/handle/190111/5177
Collection中国科学院科技政策与管理科学研究所(1985年6月-2015年12月)
Recommended Citation
GB/T 7714
He, J,Shi, Y,Xu, WX. Classifications of credit cardholder behavior by using multiple criteria non-linear programming[J]. DATA MINING AND KNOWLEDGE MANAGEMENT,2004,3327(1):10,154-163.
APA He, J,Shi, Y,&Xu, WX.(2004).Classifications of credit cardholder behavior by using multiple criteria non-linear programming.DATA MINING AND KNOWLEDGE MANAGEMENT,3327(1),10,154-163.
MLA He, J,et al."Classifications of credit cardholder behavior by using multiple criteria non-linear programming".DATA MINING AND KNOWLEDGE MANAGEMENT 3327.1(2004):10,154-163.
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