BibTeX:

@article{IJIRSTV4I1013,
     title={Credit Card Fraud Detection and Prevention - A Survey},
     author={Surbhi Gupta, Mrs. Nitima Malsa and Mr. Vimal Gupta},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={4},
     number={1},
     pages={1--7},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV4I1013.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

A credit card is a convenient tool that allows you to buy items now and pay for them later. Banking Sector involves a lot of transactions for their day to day operation and they have now realized that their main disquietude is how to detect fraud as early as possible. The credit card has become the most popular mode of payment for both online as well as regular purchase. Credit card frauds are increasing day by day regardless of various techniques developed for its detection. Fraud detection systems have become essential for all credit card issuing banks to minimize their losses. The most commonly used fraud detection methods are Artificial Immune System (AIS), Hidden Markov Model (HMM), Neural Network, Genetic Algorithms, Decision Tree and Support Vector Machine (SVM). These techniques can be used alone or in collaboration using ensemble or meta-learning techniques to build classifiers. The main objective of this paper is to review methodology of different detection methods based on credit card in terms of Parameter like Speed of detection, Accuracy and cost the comparison of mentioned approaches based on survey. This paper presents a survey of various techniques used in credit card fraud detection and prevention.

Credit Card, Credit Card Fraud, Fraud Detection Techniques, Fraud Prevention Techniques