Automating fraud detection: The essential guide

By Leigh Carmichael

Published | Monday, February 19th, 2018


Data analysis can play a critical role in identifying indicators of fraud in most business process areas. By implementing risk and control data analytics to regularly monitor business transactions—and integrating them into an overall risk and control process—management can identify and respond quickly to red flags, and reduce the risk of fraud escalation. Through a discussion of typical frauds, detection processes and tests, you will learn how to achieve results by applying data analysis software in key business areas.

During the past five or so years, surveys of senior professionals in the areas audit, risk management, compliance, and fraud detection have consistently shown that increased use of technology is considered to be a critical factor for successful performance. More specifically, the surveys have found that data analysis software is the technology that is expected to have the greatest impact on effectiveness and productivity.So, how, in practice, can data analysis software be used to improve and automate fraud detection processes and support overall risk management?

This paper identifies some of the key issues in implementing a fraud detection program and provides examples of fraud detection tests for common business process areas.

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