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A review of Fraud Detection Techniques: Credit Card
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 45 - Number 1 |
| Year of Publication: 2012 |
| Authors: Khyati Chaudhary, Jyoti Yadav, Bhawna Mallick |
10.5120/6748-8991
|
Khyati Chaudhary, Jyoti Yadav, Bhawna Mallick . A review of Fraud Detection Techniques: Credit Card. International Journal of Computer Applications. 45, 1 ( May 2012), 39-44. DOI=10.5120/6748-8991
Abstract
In present scenario when the term fraud comes into a discussion, credit card fraud clicks to mind so far. With the great increase in credit card transactions, credit card fraud has increasing excessively in recent years. Fraud detection includes monitoring of the spending behavior of users/ customers in order to determination, detection, or avoidance of undesirable behavior. As credit card becomes the most prevailing mode of payment for both online as well as regular purchase, fraud relate with it are also accelerating. Fraud detection is concerned with not only capturing the fraudulent events, but also capturing of such activities as quickly as possible. The use of credit cards is common in modern day society. Fraud is a millions dollar business and it is rising every year. Fraud presents significant cost to our economy worldwide. Modern techniques based on Data mining, Machine learning, Sequence Alignment, Fuzzy Logic, Genetic Programming, Artificial Intelligence etc. , has been introduced for detecting credit card fraudulent transactions. This paper shows how data mining techniques can be combined successfully to obtain a high fraud coverage combined with a low or high false alarm rate.
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