A Review on Credit Card Fraud Detection Techniques

Authors(6) :-Chandan Kumar, Kamlesh Parate, Shreyash Sahare, Prajakta Lokhande, Moh. Akram Beg, Prof. Rohan Kokate

The credit card has turned into the most prevalent method of instalment for both online and additionally normal buy, in instances of fraud related with it are likewise rising. Credit card frauds are expanding step by step paying little respect to different methods created for its detection. Fraudsters are experts to the point that they create better approaches for conferring fraudulent exchanges every day which requests consistent advancement for its detection methods. A large portion of the systems in light of Artificial Intelligence, Fuzzy Logic, Neural Network, Logistic Regression, Naive Bayesian, Machine Learning, Sequence Alignment, Decision tree, Bayesian system, meta learning, Genetic programming and so on., these are developed in recognizing different credit card fraudulent exchanges. This paper displays a review of different methods utilized as a part of different credit card fraud detection systems.

Authors and Affiliations

Chandan Kumar
BE Students, Department of Information Technology/Computer Science & Engineering, J. D College of Engineering and Management, Nagpur, Maharashtra, India
Kamlesh Parate
Department of Information Technology/Computer Science & Engineering, J. D College Of Engineering and Management, Nagpur, Maharashtra, India
Shreyash Sahare

Prajakta Lokhande

Moh. Akram Beg

Prof. Rohan Kokate

Credit Card Fraud, Hidden Markov Model (HMM), Fraud Detection, Password, Security Question

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Publication Details

Published in : Volume 3 | Issue 2 | January-February 2018
Date of Publication : 2018-01-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 253-257
Manuscript Number : CSEIT1833187
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Chandan Kumar, Kamlesh Parate, Shreyash Sahare, Prajakta Lokhande, Moh. Akram Beg, Prof. Rohan Kokate, "A Review on Credit Card Fraud Detection Techniques", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 2, pp.253-257, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1833187

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