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Forensic analytics : methods and techniques for forensic accounting investigations / [electronic resource]

by Nigrini, Mark J. (Mark John).
Material type: materialTypeLabelBookSeries: Wiley corporate F & A: Publisher: Hoboken, N.J. : Wiley, ©2011Description: 1 online resource (xvi, 463 pages) : illustrations.ISBN: 9781118087633; 1118087631; 9781118087664; 1118087666; 9781118087688; 1118087682; 9781118386798; 1118386795; 1283176378; 9781283176378.Subject(s): Forensic accounting | Fraud | Misleading financial statements | Social Science | LAW -- Forensic Science | Forensic accounting | Fraud | Misleading financial statements | Betrug | Rechnungslegung | Wirtschaftsprüfung | Electronic booksOnline resources: Wiley Online Library
Contents:
Front Matter -- Using Access in Forensic Investigations -- Using Excel in Forensic Investigations -- Using PowerPoint in Forensic Presentations -- High₆Level Data Overview Tests -- Benford's Law: The Basics -- Benford's Law: Assessing Conformity -- Benford's Law: The Second₆Order and Summation Tests -- Benford's Law: The Number Duplication and Last₆Two Digits Tests -- Testing the Internal Diagnostics of Current Period and Prior Period Data -- Identifying Fraud Using the Largest Subsets and Largest Growth Tests -- Identifying Anomalies Using the Relative Size Factor Test -- Identifying Fraud Using Abnormal Duplications within Subsets -- Identifying Fraud Using Correlation -- Identifying Fraud Using Time₆Series Analysis -- Fraud Risk Assessments of Forensic Units -- Examples of Risk Scoring with Access Queries -- The Detection of Financial Statement Fraud -- Using Analytics on Purchasing Card Transactions -- References -- Index.
Summary: "The book will review and discuss (with Access and Excel examples) the methods and techniques that investigators can use to uncover anomalies in corporate and public sector data. These anomalies would include errors, biases, duplicates, number rounding, and omissions. The focus will be the detection of fraud, intentional errors, and unintentional errors using data analytics. Despite the quantitative and computing bias, the book will still be interesting to read with interesting vignettes and illustrations. Most chapters will be understandable by accountants and auditors that usually are lacking in the rigors of mathematics and statistics. The data interrogation methods are based on (a) known statistical techniques, and (b) the author's own published research in the field"-- Provided by publisher.
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Includes bibliographical references and index.

Front Matter -- Using Access in Forensic Investigations -- Using Excel in Forensic Investigations -- Using PowerPoint in Forensic Presentations -- High₆Level Data Overview Tests -- Benford's Law: The Basics -- Benford's Law: Assessing Conformity -- Benford's Law: The Second₆Order and Summation Tests -- Benford's Law: The Number Duplication and Last₆Two Digits Tests -- Testing the Internal Diagnostics of Current Period and Prior Period Data -- Identifying Fraud Using the Largest Subsets and Largest Growth Tests -- Identifying Anomalies Using the Relative Size Factor Test -- Identifying Fraud Using Abnormal Duplications within Subsets -- Identifying Fraud Using Correlation -- Identifying Fraud Using Time₆Series Analysis -- Fraud Risk Assessments of Forensic Units -- Examples of Risk Scoring with Access Queries -- The Detection of Financial Statement Fraud -- Using Analytics on Purchasing Card Transactions -- References -- Index.

"The book will review and discuss (with Access and Excel examples) the methods and techniques that investigators can use to uncover anomalies in corporate and public sector data. These anomalies would include errors, biases, duplicates, number rounding, and omissions. The focus will be the detection of fraud, intentional errors, and unintentional errors using data analytics. Despite the quantitative and computing bias, the book will still be interesting to read with interesting vignettes and illustrations. Most chapters will be understandable by accountants and auditors that usually are lacking in the rigors of mathematics and statistics. The data interrogation methods are based on (a) known statistical techniques, and (b) the author's own published research in the field"-- Provided by publisher.

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Last Updated on September 15, 2019
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