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Reseach Article

Evaluating and Emerging Payment Card Fraud Challenges and Resolution

by Pankaj Richhariya, Prashant K Singh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 14
Year of Publication: 2014
Authors: Pankaj Richhariya, Prashant K Singh
10.5120/18817-0215

Pankaj Richhariya, Prashant K Singh . Evaluating and Emerging Payment Card Fraud Challenges and Resolution. International Journal of Computer Applications. 107, 14 ( December 2014), 5-10. DOI=10.5120/18817-0215

@article{ 10.5120/18817-0215,
author = { Pankaj Richhariya, Prashant K Singh },
title = { Evaluating and Emerging Payment Card Fraud Challenges and Resolution },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 14 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 5-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume107/number14/18817-0215/ },
doi = { 10.5120/18817-0215 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:41:02.151293+05:30
%A Pankaj Richhariya
%A Prashant K Singh
%T Evaluating and Emerging Payment Card Fraud Challenges and Resolution
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 14
%P 5-10
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Payment card fraud losses for the card payment industry is generating billions of dollars. In addition to direct damage, the brand name due to fraud can be affected by a lack of customer faith. These cause the deficit is rising, financial institutions and card issuers are constantly new technologies and innovative payment card fraud detection and prevention are demanding. Fraudsters, customers and defense organizations around the world is applied various resolution financial institutions, payment card fraud. The solution is better spent on risk management techniques to predict label use, and customer experience management are designed with the aim of preventing losses. By retaining the right balance between these purposes operational risk management philosophy is driven by a firm. The aim is to protect the gainful customers by delivering them with a stable positive experience. This paper deliberates the solution of payment card fraud and discuss the various attributes of an effective payment card and its applied thoughts. Inspite of this, paper also reviews challenges, the concepts associated to the profiling of card-holder, advanced analytics, metrics to be followed, and mechanisms of the resolution of card fraud.

References
  1. Ogwueleka, F. N. 2008. Credit card fraud detection using data mining techniques. Ph. D. Dissertation. Department of Computer Science. Nnamdi Azikiwe University, Awka Nigeria.
  2. Maes, S. ; Tuyls, K. ; Vanschoenwinkel, B. ; and Manderick, B. 2002. Credit card detection using Bayesian and neural networks. Proceeding International NAISO Congress on neuron fuzzy Technologies.
  3. Bhatla T. P. ; Prabhu, V. ; and Dua, A. 2003. Understanding credit card frauds. Cards Business Review# 2003-1, Tata Consultancy Services.
  4. Adnan M. Al-Khatib. 2007. "Mining Fraudulent Behavior in e-payment Systems"; Ph. D. Dissertation.
  5. Clifton Phua; "Minority Report in Fraud Detection: Classification of Skewed Data"; Sigkdd Explorations, Vol. 6.
  6. Salvatore J. Stolfo. 1997. "Credit Card Fraud Detection Using Meta-Learning "; Columbia University.
  7. Salvatore J. Stolfo and Wei Fan 1999. "Cost-based Modelling for Fraud and Intrusion Detection: Results from the JAM Project"; Columbia University; 0-7695-0490-6/99, IEEE.
  8. V. Dheepa, R. Dhanapal and D. Religious. 2010. "A Novel Approach to Credit Card Fraud Detection Model", Journal of Computing, Vol. 2, No. 12, pp. 96.
  9. Chan, P. and Stolfo, S. (1998): Toward scalable learning with non-uniform class and cost distributions: A case study in credit card fraud detection. Proc. of the Fourth International Conference on Knowledge Discovery and Data Mining, pp. 164–168.
  10. Mena, J: (2003) Investigate Data mining for security and criminal Detection, Butterworth- Heinemann, Amsterdam.
Index Terms

Computer Science
Information Sciences

Keywords

Payment card fraud fraud detection behavior patterns.