The book starts by differentiating forensic accounting from traditional auditing, then explores legal and ethical considerations. It details various fraud schemes like asset misappropriation, corruption, and financial statement fraud, providing methods for their detection. The text progresses through evidence gathering, interviewing techniques, and documentation, culminating in preventative controls and fraud risk management programs.
Practical case studies and real-world examples are used throughout. A key takeaway is the practical guidance offered, including checklists, interview templates, and data analysis techniques applicable in real-world scenarios. Furthermore, the book introduces innovative models for integrating AI and machine learning into fraud detection systems, making it a valuable resource for auditors, accountants, fraud examiners, and corporate executives focused on risk management and internal controls.