A Survey on Different Data Mining & Machine Learning Methods for Credit Card Fraud Detection

Authors

  • Vipul Patil  M. Tech Scholar Department of CSE NIIST Bhopal, Madhya Pradesh, India
  • Dr. Umesh Kumar Lilhore   Head Department of CSE NIIST Bhopal, Madhya Pradesh, India

Keywords:

Data Mining, Machine Learning, Credit Card Fraud, Cashless Transactions.

Abstract

Due to rapid growth in field of cashless or digital transactions, credit cards are widely used in all around the world. Credit cards providers are issuing thousands of cards to their customers. Providers have to ensure all the credit card users should be genuine and real. Any mistake in issuing a card can be reason of financial crises. Due to rapid growth in cashless transaction, the chances of number of fraudulent transactions can also increasing. A Fraud transaction can be identified by analyzing various behaviors of credit card customers from previous transaction history datasets. If any deviation is noticed in spending behavior from available patterns, it is possibly of fraudulent transaction. Data mining and machine learning techniques are widely used in credit card fraud detection. In this survey paper we are presenting review of various data mining and machine learning methods which are widely used for credit card fraud detections.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-06-30

Issue

Volume 3, Issue 5, May-June-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Vipul Patil, Dr. Umesh Kumar Lilhore , " A Survey on Different Data Mining & Machine Learning Methods for Credit Card Fraud Detection, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.320-325, May-June-2018.