Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations

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John Wiley & Sons, May 12, 2020 - Business & Economics - 544 pages

Become the forensic analytics expert in your organization using effective and efficient data analysis tests to find anomalies, biases, and potential fraud—the updated new edition

Forensic Analytics reviews the methods and techniques that forensic accountants can use to detect intentional and unintentional errors, fraud, and biases. This updated second edition shows accountants and auditors how analyzing their corporate or public sector data can highlight transactions, balances, or subsets of transactions or balances in need of attention. These tests are made up of a set of initial high-level overview tests followed by a series of more focused tests. These focused tests use a variety of quantitative methods including Benford’s Law, outlier detection, the detection of duplicates, a comparison to benchmarks, time-series methods, risk-scoring, and sometimes simply statistical logic. The tests in the new edition include the newly developed vector variation score that quantifies the change in an array of data from one period to the next. The goals of the tests are to either produce a small sample of suspicious transactions, a small set of transaction groups, or a risk score related to individual transactions or a group of items.

The new edition includes over two hundred figures. Each chapter, where applicable, includes one or more cases showing how the tests under discussion could have detected the fraud or anomalies. The new edition also includes two chapters each describing multi-million-dollar fraud schemes and the insights that can be learned from those examples. These interesting real-world examples help to make the text accessible and understandable for accounting professionals and accounting students without rigorous backgrounds in mathematics and statistics. Emphasizing practical applications, the new edition shows how to use either Excel or Access to run these analytics tests. The book also has some coverage on using Minitab, IDEA, R, and Tableau to run forensic-focused tests. The use of SAS and Power BI rounds out the software coverage. The software screenshots use the latest versions of the software available at the time of writing. This authoritative book:

  • Describes the use of statistically-based techniques including Benford’s Law, descriptive statistics, and the vector variation score to detect errors and anomalies
  • Shows how to run most of the tests in Access and Excel, and other data analysis software packages for a small sample of the tests
  • Applies the tests under review in each chapter to the same purchasing card data from a government entity
  • Includes interesting cases studies throughout that are linked to the tests being reviewed.
  • Includes two comprehensive case studies where data analytics could have detected the frauds before they reached multi-million-dollar levels
  • Includes a continually-updated companion website with the data sets used in the chapters, the queries used in the chapters, extra coverage of some topics or cases, end of chapter questions, and end of chapter cases.

Written by a prominent educator and researcher in forensic accounting and auditing, the new edition of Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations is an essential resource for forensic accountants, auditors, comptrollers, fraud investigators, and graduate students.


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Very interesting concept and just started reading out of necessity to understand why the common acceptance of failing politicians to corruption is permitted psychologically in society.
with best regards;


Using Microsoft Excel for Forensic Analytics
The Initial HighLevel Overview Tests
Benfords Law The Basic Tests
Benfords Law Advanced Topics
Benfords Law Completing The Cycle
Identifying Anomalous Outliers Part 1
Identifying Anomalous Outliers Part 2
Identifying Anomalies In TimeSeries Data
Scoring Forensic Units for Fraud Risk
Case Study An Employees
Fraudulent Shipping Claims
Detecting Financial Statement Fraud
Using Microsoft Access and R For Analytics
Concluding Notes on Fraud Prevention

Identifying Abnormal Duplications
Comparing Current Period
Comparing Current Period

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About the author (2020)

MARK J. NIGRINI, PHD, is a professor at West Virginia University where he teaches highly-rated, graduate-level accounting technology and forensic accounting classes. He has published extensively in academic and professional journals on various topics related to forensic analytics. His current research addresses forensic and continuous monitoring techniques and advanced theoretical work on Benford's Law.

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