Discover how to detect fraud, biases, or errors in your data using Access or Excel With over 300 images, Forensic Analytics reviews and shows how twenty substantive and rigorous tests can be used to detect fraud, errors, estimates, or biases in your data. For each test, the original data is shown with the steps needed to get to the final result. The tests range from high-level data overviews to assess the reasonableness of data, to highly focused tests that give small samples of highly suspicious transactions. These tests are relevant to your organization, whether small or large, for profit, nonprofit, or government-related. * Demonstrates how to use Access, Excel, and PowerPoint in a forensic setting * Explores use of statistical techniques such as Benford's Law, descriptive statistics, correlation, and time-series analysis to detect fraud and errors * Discusses the detection of financial statement fraud using various statistical approaches * Explains how to score locations, agents, customers, or employees for fraud risk * Shows you how to become the data analytics expert in your organization Forensic Analytics shows how you can use Microsoft Access and Excel as your primary data interrogation tools to find exceptional, irregular, and anomalous records.
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Mark J. Nigrini, PhD, is an Associate Professor at The College of New Jersey, where he teaches auditing and forensic accounting. His current research addresses forensic and continuous monitoring techniques and advanced theoretical work on Benford's Law. Dr. Nigrini has published his Benford's Law and forensic accounting research in academic journals and in professional accounting and auditing publications. He has been interviewed on radio and television and his work has been discussed in publications including the Wall Street Journal and the New York Times.
Discover how to detect fraud, biases, or errors in your data using Access or Excel
Every fraud or error changes your data in some way or another. The challenge is to find those needles in the haystack. Forensic Analytics shows how you can use Microsoft Access and Excel as your primary interrogation tools to find exceptional, irregular, and anomalous transactions.
Forensic Analytics reveals how you can:
With over 300 images, Forensic Analytics reviews and shows how twenty tests can be used to detect fraud, errors, or biases in your data. For each test, the original data is shown together with the steps needed to get to the final result. The tests range from thorough overviews to assess the reasonableness of data, to highly focused tests that give small samples of highly suspicious transactions. Some tests incorporate time and changes over time while other tests look for irregular patterns, excessively large amounts, or excessive duplications. The tests are relevant to any kind or size organization, whether small or large, nonprofit, or government-related.
FORENSIC ANALYTICS
Methods and Techniques for Forensic Accounting Investigations
Forensic analytics is the use of electronic data to reconstruct or detect financial fraud. The process of forensic analytics is made up of data collection and preparation, data analysis, and the preparation of a fraud report and the possible presentation of the results.
In Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations, author Mark Nigrini reviews the use of Microsoft Access and Excel in a forensic setting, together with many rigorous analytical procedures to detect employee fraud, biases, and other irregularities including errors. The book includes a comprehensive chapter on financial statement fraud, and the concluding chapter on credit/debit purchasing card fraud shows an authentic dashboard used by a Fortune 100 company.
Nigrini devotes three chapters to a review of the use of Access, Excel, and PowerPoint in a forensic setting. The next eleven chapters discuss data interrogation tests that could be used in a forensic setting to detect employee fraud, biases, and errors. In each chapter, the tests are discussed in general terms and are then demonstrated using case studies with real data. In addition, the steps needed to run the tests are illustrated with screenshots from Access and Excel. Two chapters review, with examples, a risk-scoring technique that can be used to score divisions, agents, or locations for fraud risk.
A full chapter presents various tests, along with real-world examples and case studies, to detect financial statement fraud. The concluding chapter is a case study showing an analysis of purchasing card data using selected tests from the prior chapters, and a presentation of the findings.
The companion website (www.nigrini.com/ForensicAnalytics.htm) has all the data tables used in the book, available for download. Along with notes and updates related to the book, the website also includes end-of-chapter problems and assignments for use by instructors, together with PowerPoint slides for presentations.
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