Abstract

Now a day, credit card transaction is one the famous mode for financial transaction. Increasing trends of financial transactions through credit cards also invite fraud activities that involve the loss of billions of dollars globally. It is also been observed that fraudulent transactions have increased by 35% from 2018. A huge amount of transaction data is available to analyze the fraud detection activities that require analysis of behavior/abnormalities in the transaction dataset to detect and ignore the undesirable action of the suspected person. The proposed paper lists a compressive summary of various techniques for the classification of fraud transactions from the various datasets to alert the user for such transactions.

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