Forensic analytics : methods and techniques for forensic accounting investigations / Mark J. Nigrini
Material type:
- 9780470890462
- HV 6768 .N54 2011

Item type | Current library | Home library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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National University - Manila | LRC - Main General Circulation | Digital Forensic | GC HV 6768 .N54 2011 (Browse shelf(Opens below)) | c.1 | Available | NULIB000008365 |
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GC HF 5548.37 .L36 2016 Information security policies, procedures, and standards : a practitioner's reference / | GC HM 742 .A27 2010 Facebook for dummies / | GC HV 6691 .N54 2012 Benford's law : applications for forensic accounting, auditing, and fraud detection / | GC HV 6768 .N54 2011 Forensic analytics : methods and techniques for forensic accounting investigations / | GC HV 6768 .P39 2013 c.1 White-collar crime : the essentials / | GC HV 6768 .P39 2013 c.2 White-collar crime : the essentials / | GC HV 677 .B74 2010 c.1 Cybercrime : criminal threats from cyberspace / |
Includes bibliographical references and index.
Front Matter -- Using Access in Forensic Investigations -- Using Excel in Forensic Investigations -- Using PowerPoint in Forensic Presentations -- HighΓéåLevel Data Overview Tests -- Benford's Law: The Basics -- Benford's Law: Assessing Conformity -- Benford's Law: The SecondΓéåOrder and Summation Tests -- Benford's Law: The Number Duplication and LastΓéåTwo 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 TimeΓéåSeries 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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