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

Acknowledgments

I WOULD LIKE TO THANK Athena Mailloux, who developed my interest in occupational fraud and fraud detection. Without her insistence that I join her in teaching a financial-fraud program that she developed for a local college, I would not have found the enthusiasm for fraud detection.

Alain Soublière and all the wonderful people at CaseWare IDEA Inc. deserve much credit for their assistance, support, and professionalism. CaseWare IDEA allowed me to combine fraud detection with data analytics.

A special thanks to Brian Element, an IDEAScript master. Without Brian, the automated IDEAScripts offered in the companion website would not exist. I met Brian, a chartered professional accountant, at an advanced IDEA course that he presented in 2011. We started chatting and it came out the Brian wanted to learn IDEAScripting. Brian said that he would have to come up with a scenario for his self-learning IDEAScript project. At the time, I had given much thought to the detection of anomalies through the use of data analytics, so I said to him, “Have I got a deal for you!” Since that time we have been working together on ideas for scripts for fraud detection that Brian programs. From self-learning, Brian has become the world’s leading expert in IDEAScripts and he has been conferred the certified IDEAScript expert (CISE) designation by CaseWare IDEA. At the time of writing, Brian is the sole holder of this designation.

Most important, I would like to thank my family, friends, ...