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Title |
Detection of credit card fraud: State of art |
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Author |
Imane Sadgali, Nawal Sael and Faouzia Benabbou |
| Citation |
Vol. 18 No. 11 pp. 76-83 |
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Abstract |
Credit card fraud is costing the payment card industry, literally billions of dollars annually. Financial institutions try to improve continually their fraud detection systems, but fraudsters are in same time inventing new techniques to hack systems. That said the prevention and detection of credit card fraud become an emergency. Data mining techniques are providing great help in financial fraud detection, since dealing with the large and complex among of financial data are big challenges for financial institutions. In recent years, several studies have used machine learning and data mining techniques to face this problem. In this paper, we propose a state of the art on various techniques of credit card fraud detection. The purpose of this study is to give a review of implemented techniques for credit card fraud detection, analyse their incomes and limitless, and synthesise the finding in order to identify the techniques and methods that give the best results so far. |
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Keywords |
Fraud Detection, Financial Fraud, Machine-Learning, Credit Card |
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