Forensic analytics : methods and techniques for forensic accounting investigations / Mark J. Nigrini.
Material type:
TextPublication details: Hoboken, N.J. : Wiley, 2020Edition: 2nd edDescription: xvi, 505 p. : ill. ; 26 cmISBN: - 9781119585763
- 363.25/963 22
- HV6768 .N54 2020
- BUS003000
| Item type | Current library | Collection | Call number | Vol info | Status | Date due | Barcode | |
|---|---|---|---|---|---|---|---|---|
Main Long
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Martin Oduor-Otieno Library This item is located on the library first floor | Non-fiction | HV6768 .N54 2020 (Browse shelf(Opens below)) | 32073/25 | Available | MOOL25070002 |
Browsing Martin Oduor-Otieno Library shelves, Shelving location: This item is located on the library first floor, Collection: Non-fiction Close shelf browser (Hides shelf browser)
| HV6695 .B35 2017 Fraud : an American history from Barnum to Madoff / | HV6768 .H66 2005 Money laundering : a concise guide for all business / | HV6768 .N54 2020 Forensic analytics : methods and techniques for forensic accounting investigations / | HV6768 .N54 2020 Forensic analytics : methods and techniques for forensic accounting investigations / | HV6773 .C916 2011 Cyber criminology : exploring Internet crimes and criminal behavior / | HV7936.P8 L45 2003 Policing and media : | HV8079.C65 N45 2019 Guide to computer forensics and investigations / |
Includes bibliographical references and 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"--
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