Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations - Second Edition
This updated second edition provides forensic accountants and auditors with proven data analysis methods to detect errors, fraud, and biases in corporate and public sector data. The book demonstrates how to identify suspicious transactions, balances, and anomalies through statistically-based testing techniques.
Core Analytical Methods Covered
The text presents a comprehensive framework of forensic analytics tests, starting with high-level overview assessments and progressing to focused analytical procedures. Key methods include Benford's Law applications, outlier detection, duplicate identification, benchmark comparisons, time-series analysis, risk-scoring techniques, and the newly developed vector variation score that quantifies data changes between periods.
Practical Software Implementation
Each analytical test includes practical guidance for implementation using Excel and Access, with additional coverage of Minitab, IDEA, R, Tableau, SAS, and Power BI. The book features over two hundred figures and screenshots using the latest software versions, making complex statistical concepts accessible for accounting professionals without advanced mathematics backgrounds.
Real-World Case Studies and Applications
The book applies forensic tests to actual purchasing card data from a government entity throughout multiple chapters, providing consistent practical context. Two comprehensive chapters examine multi-million-dollar fraud schemes, demonstrating how data analytics could have detected these frauds at early stages. Additional case studies in each chapter show how the discussed tests could have identified real-world fraud and anomalies.
What's Included
- Statistically-based techniques including Benford's Law, descriptive statistics, and vector variation score applications
- Step-by-step instructions for running tests in multiple data analysis software packages
- Consistent application of tests to the same dataset throughout chapters for comparative learning
- Multi-million-dollar fraud case studies with detailed analytical insights
- Continually-updated companion website with datasets, queries, supplemental coverage, and end-of-chapter questions and cases
