Vona - Fraud data analytics methodology: the fraud scenario approach to uncovering fraud in core business systems

1. Chapter 1
2. Chapter 2
3. Chapter 3
4. Chapter 4
5. Chapter 5
6. Chapter 6
7. Chapter 7

Copyright 2017 by John Wiley & Sons, Inc. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey.

Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data:

Names: Vona, Leonard W., 1955- author.

Title: Fraud data analytics methodology : the fraud scenario approach to uncovering fraud in core business systems / Leonard W. Vona.

Description: Hoboken, New Jersey : John Wiley & Sons, [2017] | Includes index.

Identifiers: LCCN 2016036161 | ISBN 9781119186793 (cloth) | ISBN 9781119270348 (ePDF) | ISBN 9781119270355 (epub)

Subjects: LCSH: Auditing. | Forensic accounting. | FraudPrevention. | Auditing, Internal.

Classification: LCC HF5667 .V659 2017 | DDC 658.4/73dc23

LC record available at https://lccn.loc.gov/2016036161

Cover design: Wiley

Cover image: kentoh/Shutterstock

The Wiley Corporate F&A series provides information, tools, and insights to corporate professionals responsible for issues affecting the profitability of their company, from accounting and finance to internal controls and performance management.

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This book is dedicated to my family, Patricia, Amy, David, and Jeffrey, for supporting me in my quest to explain fraud auditing. In the memory of my dad, who told me to go to college, and the memory of the women who shaped my life.

Even the world's best auditor using the world's best audit program cannot detect fraud unless their sample includes a fraudulent transaction. That is why fraud data analytics is so essential to the auditing profession.

Fraud auditing is a methodology tool used to respond to the risk of fraud in core business systems. The methodology must start with the fraud risk identification. Fraud data analytics is about searching for a fraud scenario versus a data anomaly. I have often referred to fraud data analytics as code breaking. The fraud auditor is studying millions of transactions in the attempt to find the needle in the haystack, called the fraud scenario. It is my hope that my years of professional experience in using fraud data analytics will move the auditing profession to become the numberone reason for fraud detection.

This book is about the science of fraud data analytics. It is a systematic study of fraud scenarios and their relationship to data. Like all scientific principles, the continual study of the science and the practical application of the science are both necessary for success in the discovery of fraud scenarios that are hiding in all core business systems.

The methodology described in the book is intended to provide a stepbystep process for building the fraud data analytics plan for your company. The first five chapters explain each phase of the process. Later chapters illustrate how to implement the methodology in asset misappropriation schemes, corruption schemes, and financial reporting schemes.

The practitioner will learn that fraud data analytics is both a science and an art. In baseball, there is a science to hitting a baseball. The mechanics of swinging a bat is taught to players of all ages. However, you can read all the books in the world about swinging a bat, but unless you actually stand in the batting box and swing the bat, you will never truly learn the art of hitting a baseball. Likewise, the fraud auditor needs to learn to analyze data and to employ the tools to do so in order to be able to find fraud scenarios hiding in your data systems.

To my friends at Audimation Services: Carolyn Newman, Jill Davies, and Carol Ursell. It is because of working with you that I developed the art of fraud data analytics.

To Sheck Cho (Executive Editor), who encouraged me to write my books, and to the editors at Wiley, without you I could not have written this book.

To Nicki Hindes, who keeps my office going while I travel the world.

To all those people who have inspired me. Thank you!

The world's best auditor using the world's best audit program cannot detect fraud unless their sample includes a fraudulent transaction. This is why fraud data analytics (FDA) is so critical to the auditing profession.

How we use fraud data analytics largely depends on the purpose of the audit project. If the fraud data analytics is used in a whistle blower allegation, then the fraud data analytics plan is designed to refute or corroborate the allegation. If the fraud data analytics plan is used in a control audit, then the fraud data analytics would search for internal control compliance or internal control avoidance. If the fraud data analytics is used for fraud testing, then the fraud data analytics is used to search for a specific fraud scenario that is hidden in your database. This book is written for fraud auditors who want to integrate fraud testing into their audit program. The concepts are the same for fraud investigation and internal control avoidancewhat changes is the scope and context of the audit project.