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Author:
Nigrini, Mark J. (Mark John)
Title:
Forensic analytics : methods and techniques for forensic accounting investigations / Mark J. Nigrini, B.Com. (Hons), MBA, Ph.D.
Edition:
Second Edition.
Publisher:
Wiley,
Copyright Date:
2020
Description:
1 volume : illustrations.
Subject:
Forensic accounting.
Fraud.
Misleading financial statements.
Forensic accounting.
Fraud.
Misleading financial statements.
Notes:
Revised edition of the author's Forensic analytics, c2011. Includes bibliographical references and 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. New to this edition are: Updates to Windows and Microsoft Office R, which is now a viable data analytics product. New fraud cases There are many published books on data mining, which is defined as the analysis of (large) data sets to find unsuspected relationships, and to summarize the data in novel ways that are both understandable and useful to the data owner. The results of such analyses could be sales predictions or discovering previously unknown patterns and rules. Data mining involves using the data for some specific purpose (often tied to marketing) but typically has no fraud detection motive. Yet, data mining can be a valuable tool to detect errors and anomalies that can lead to the discovery of fraud"-- Provided by publisher.
Series:
Wiley corporate f&a
ISBN:
1119585767
9781119585763
OCLC:
(OCoLC)1143841569
LCCN:
2019056749
Locations:
OVUX522 -- University of Iowa Libraries (Iowa City)

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