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Fraud and Fraud Detection: A Data Analytics Approach, + Website

ISBN: 978-1-118-77965-1

November 2014

352 pages

Description

Big data and other emerging technologies can be a fraudster's dream come true. It's a cinch to hide a few fraudulent transactions within enormous, difficult-to-manage databases. And tech-savvy fraudsters can use new software to automate their risky activities. Unhappily for them, big data can also simplify the process of fraud detection. That's where Fraud and Fraud Detection comes in, showing auditors, investigators, and risk professionals how to use big data analytics to stay one step ahead of cyber criminals.

Only a tiny fraction of businesses worldwide are using big data technologies to aid in fraud detection. Why? One reason could be the lack of clear resources supporting the implementation of a fraud mitigation approach that is still on the cutting-edge. Fraud and Fraud Detection goes a very long way toward removing this obstacle. This hands-on book addresses all the major types of employee fraud, including cash skimming, billing schemes, payroll fraud, and many more. For each fraud type, author Sunder Gee provides tests that can be customized and automated, even for millions of transactions per day.

Data analytics software is a crucial element in bringing fraud detection into the 21st century. The techniques in Fraud and Fraud Detection can be used with any analytics software, and there is enough information here to develop a step-by-step plan for designing and implementing automated detection programs. Users of CaseWare's IDEA software will especially appreciate the downloadable IDEAScripts that can speed the process of making fraud detection automatic. On the companion website included with Fraud and Fraud Detection, readers have access to a fully functional version of IDEA.

A certain amount of fraud risk is acceptable in any organization—and Sunder Gee demonstrates this point artfully in Fraud and Fraud Detection. Still, fraudsters are evolving with the times, and fraud mitigation professionals need to keep up. Right now, there is enormous potential to improve the efficiency of fraud detection through big data analytics, but almost no one is taking advantage of this opportunity. Fraud and Fraud Detection opens up a clear path for accessing this untapped value.

About the Author

SUNDER GEE spent much of his career at the Canada Revenue Agency, including holding the position of Electronic Commerce Audit Advisor for the Head Office. He has advised tax authorities around the world on the topic of computer-assisted audit techniques (CAAT). Sunder has prepared widely respected corporate training material and college courses on forensic accounting, anti–money laundering, and data analytics.