An intelligent approach to detecting the bad credit card accounts

  • Authors:

  • Yo-Ping Huang;Chun-Chieh Lu;Tsun-Wei Chang;Maw-Sheng Horng

  • Affiliations:

  • Department of Computer Science and Engineering, Tatung University, Taipei, Taiwan;Department of Computer Science and Engineering, Tatung University, Taipei, Taiwan;Department of Computer Science and Engineering, Tatung University, Taipei, Taiwan;Dept. of Mathematics and Information Education, National Taipei University of Education, Taipei, Taiwan

  • Venue:
  • AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
  • Year:
  • 2007

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Abstract

The goal of this paper is to design an intelligent model to detect the bad accounts timely. Due to the emergence of bad accounts that results in loss of billions of dollars in the issuers each year, several modern techniques in detecting the bad credit card accounts are continually evolved and applied to the credit card industry. The detection of bad credit card accounts has advanced considerably from its early reliance on historical delinquency rates and charge-off trend analyses. This paper presents an intelligent model to detect the bad credit card accounts, where artificial intelligence (AI) techniques such as fuzzy logic (FL) and backpropagation neural network (BPN) are combined to achieve a more accurate problem detector with a higher availability. Experimental results are given to verify the effectiveness of the proposed model.