Help your students understand the growing significance of fraud in today's accounting world as the latest edition of this engaging text teaches how to identify, detect, investigate, and prevent financial fraud. Forensic Accounting 4/e closely examines the nature of fraud using memorable business examples and captivating actual fraud including recent developments in e-business fraud. Students explore how technology is increasingly involved in fraud and how it can be used to detect fraud as well as what the legal options are for victims of fraud. Significant new discussion of forensic analysis expands students' understanding of the field, while a fresh, clean design increases readability and student appeal. New learning features and strong end-of-chapter exercises draw attention to the most important information and drive critical thinking.
Proven end-of-chapter materials: Actual fraud cases drawn from first-hand experience providing intriguing opportunities to apply concepts, while additional end-of-chapter exercises offer helpful practice and review.
Strong emphasis on fraud detection, prevention, and investigation: A variety of information on preventing, detecting, and investigating fraud examines the nature of fraud perpetrators and why they commit fraud. Students learn to recognize the warning signs that fraud may occur as well as how to use technology most effectively to search proactively for fraud.
Authors' expertise in forensic accounting, fraud examination, and technology combines talents with innovative experts in fraud investigation technology to fill this edition with a wealth of intriguing cases and first-hand examples drawn from today's business.
Table of Contents Part 1: INTRODUCTION 1. The Nature of Fraud.
Part 2: TYPES OF FRAUD 2. Financial Statement Frauds 3. Revenue- and Inventory-Related Financial Statement Frauds. 4. Liability, Asset, and Inadequate Disclosure Frauds 5. E-Commerce Fraud 6. Bankruptcy, Divorce, and Tax Fraud 7. Consumer Fraud 8. Fraud against Organizations
Part 3: Fraud Prevention and Detection 9. Who Commits Fraud and Why 10. Fighting Fraud: An Overview 11. Preventing Fraud 12. Recognizing the Symptoms of Fraud 13. Data-Driven Fraud Detection