Fraud Detection Using Data Analytics in the Banking Industry
DISCUSSION WHITEPAPER Fraud Detection Using data Analytics in the Banking Industry2DISCUSSION PAPERTable of ContentsWHAT IS Fraud ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3WHO IS RESPONSIBLE FOR Fraud Detection ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3WHY USE data ANALYSIS FOR Fraud Detection ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4ANALYTICAL TECHNIQUES FOR Fraud Detection .
5 ISCSSI PAPER Analytical Techniques for Fraud Detection Getting started requires an understanding of: The areas in which fraud can occur What fraudulent activity would look like in the data What data sources are required to test for indicators of fraud “ACL Analytics Exchange leverages ACL’s proven analytical strengths to provide auditors with a means to
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