Data Analysis for Internal Controls, Fraud Detection, Monitoring, and Audit

(2 customer reviews)

ISBN: 978-0-9959994-0-4
278 pages
July 2017

Note: This book is exclusively sold through this website. All prices in Canadian dollars. Click Add to cart to purchase.

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The book contains numerous examples of how to perform data analysis to identify risk, uncover fraud, find control weakness, and improve efficiency and effectiveness of business operations. The actual savings from the real-life examples herein totalled more than $1B. In addition, the recommendations resulted in better controls. improved efficiency and effectiveness, reduction of risk, and higher level of assurance.

The test also contains lessons-learned that will help to move you along the learning curve by benefiting from my mistakes and 30+ years of experience performing data analysis.

The examples include analytics in the areas of risk identification and assessment, finance, IT, human resources, environment, inventory, payroll, accounts payable, accounts receivable, contracting, P-Cards, telecommunications, transportation, security, system development and conversion, travel and entertainment, medical claims, and much more.

The book also contains submissions from ten of the world’s leading experts in data analysis.

A must read for new and experienced data analysts.

Additional information

Weight .430 kg
Dimensions 22.86 × 17.78 × 1.5 cm

This article has 2 Comments

  1. I recently purchased this book and found it to be an excellent collection of success stories on how data analytics can be applied to different audit scenarios. Dave provides specific logic and ACL commands behind each of his analytics and the dollars that he has saved his companies through the use of ACL is quite impressive. If you’re looking to get some inspiration on where to go with your next analytic project, this should definitely be on your reading list!

  2. Highly recommended. How do we use this book? We read several chapters per week and then meet to go through the lessons learned and discuss what we can use/implement. I’ve also quoted from this book at a few presentations. The book is not heavy in technical material but is good balance of great ideas, words of wisdom and the history of an experienced data analyst.

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