Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations (second edition) by Mark J. Nigrini is worth a look by management accountants and other finance and audit professionals for several reasons. For one, Nigrini’s style is straightforward, and his tips are practical and relevant for practitioners. His stepwise instructions make it easy for investigators and finance professionals alike to follow. The forensic accounting and analytics techniques that he discusses are accessible to most accountants. Since I once missed out on an attractive job because I lacked investigative experience, I wish I had read this comprehensive reference work years ago.   The hook for wider audiences comes from the first word of the title: forensics. We’re drawn in by detective stories and narratives centering on fraud or other crimes. Safekeepers of a company’s assets and auditors will perk up at the second word: analytics. Do we all need advanced tools and special training to detect and investigate fraud? Nigrini asserts that most analytical investigative techniques are relevant to accounting professionals.   The book presents more than 30 interesting fraud cases that illustrate analytics tests. Some are high-level tests to detect major issues such as embezzlement, whereas others identify smaller subsets of high-risk transactions. If the organizations had embedded controls or if these tests had been run by internal, tax, or revenue-recovery auditors, then the fraud schemes detailed in the book probably would have been discovered sooner. Cases are brought to life with figures, tables, actual data, and photos.   Nigrini analyzes real-world data sets to demonstrate analytics techniques. Chapter 13 describes a $49.3 million case where an employee processed fraudulent property tax refunds. Chapter 14 describes a $20.6 million case where a supplier claimed fraudulent shipping charges. Chapter 15 is an in-depth look at financial statement fraud. The common thread running through the featured cases is that the schemes were quite simple.   The forensic analytics tests are easy to understand and run. Most of the tests are demonstrated in Excel and Access, while some are in data analysis tool IDEA, programming languages R and SAS, data visualization software Tableau, and statistics software package Minitab. Considering all the valuable information and relevant examples in the book, the techniques outlined in Forensic Analytics are worth adding to your repertoire, either to detect misconduct or enhance your understanding of data analysis for the benefit of your organization and your career.  

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