Forensic analytics methods and techniques for forensic accounting investigations /

"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 dete...

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Bibliographic Details
Main Authors: Nigrini, Mark J. Mark John
Published:
Literature type: Electronic eBook
Language: English
Series: Wiley corporate F & A
Subjects:
Online Access: http://onlinelibrary.wiley.com/book/10.1002/9781118386798
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 lack
Carrier Form: 1 online resource (xvi, 463 pages) : illustrations.
Bibliography: Includes bibliographical references and index.
ISBN: 9781118087633
1118087631
9781118087664
1118087666
9781118087688
1118087682
9781118386798
1118386795
Index Number: HV6768
CLC: D917
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