Detecting and Preventing Fraud with Data Analytics

By Leigh Carmichael

Published | Tuesday, June 12th, 2018


For many organizations, the reaction to recent market activities is resulting in lean staff, spending freezes, and a reactive approach to the continued fallout of the economic meltdown.

A shaky economy is rife with fraudulent activity. Our customers are talking about internal fraud from employee abuse of purchasing cards to large-scale fraud involving high-value
contracts and breaches of controls that could have serious consequences to businesses. This is precisely the time to step up fraud prevention and detection measures.

The primary reason to use data analytics to tackle fraud is because a lot of internal control systems have serious control weaknesses. In order to effectively test and monitor internal controls,
organizations need to look at every transaction that takes place and test them against established parameters, across applications, across systems, from dissimilar applications and data sources. Most internal control systems simply cannot handle this.

This e-book is focused on using data analytics to implement a successful fraud program, including key considerations and techniques for detecting fraud with a number of
examples that you can apply in your organization.

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