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New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection

New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection

Addisson Salazar, Gonzalo Safont, Alberto Rodriguez, Luis Vergara
Copyright: © 2018 |Pages: 14
ISBN13: 9781522522553|ISBN10: 1522522557|EISBN13: 9781522522560
DOI: 10.4018/978-1-5225-2255-3.ch428
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MLA

Salazar, Addisson, et al. "New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection." Encyclopedia of Information Science and Technology, Fourth Edition, edited by Mehdi Khosrow-Pour, D.B.A., IGI Global, 2018, pp. 4937-4950. https://doi.org/10.4018/978-1-5225-2255-3.ch428

APA

Salazar, A., Safont, G., Rodriguez, A., & Vergara, L. (2018). New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection. In M. Khosrow-Pour, D.B.A. (Ed.), Encyclopedia of Information Science and Technology, Fourth Edition (pp. 4937-4950). IGI Global. https://doi.org/10.4018/978-1-5225-2255-3.ch428

Chicago

Salazar, Addisson, et al. "New Perspectives of Pattern Recognition for Automatic Credit Card Fraud Detection." In Encyclopedia of Information Science and Technology, Fourth Edition, edited by Mehdi Khosrow-Pour, D.B.A., 4937-4950. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2255-3.ch428

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Abstract

Automatic credit card fraud detection (ACCFD) is a challenge issue that has been increasingly studied considering expanded potential of new technologies to emulate legitimate operations. Solution has to handle with fraud behavior changing in time; detection in data with very small fraud/legitimate operations ratio; and accomplish operation requirements of very low false alarm in real-time processing. In this chapter, main issues related with the problem of ACCFD and proposed solutions are discussed from theoretical and practical standpoints. The perspective of detection analyses from receiving operating characteristic curves and business key performance indicators are jointly analyzed. A new conceptual framework for ACCFD considering decision fusion and surrogate data is outlined including a case of study with different proportions of real and surrogate data. In addition, the sensitivity of the methods to different proportions of fraud/legitimate ratios is tested. Finally, theoretical and practical conclusions are provided as well as several open lines of research are proposed.

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