LEADER 03107nam 2200529 450 001 9910794161603321 005 20200803122117.0 010 $a1-119-58590-2 010 $a1-119-58587-2 035 $a(CKB)4100000010953637 035 $a(MiAaPQ)EBC6174018 035 $a(CaSebORM)9781119585763 035 $a(JP-MeL)3000131686 035 $a(Au-PeEL)EBL6174018 035 $a(OCoLC)1143818259 035 $a(EXLCZ)994100000010953637 100 $a20200803d2020 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aForensic analytics $emethods and techniques for forensic accounting investigations /$fMark J. Nigrini 205 $aSecond edition. 210 1$aHoboken, New Jersey :$cWiley,$d[2020] 210 4$d2020 215 $a1 online resource (547 pages) 225 1 $aWiley corporate F & A series 300 $aPrevious edition: 2011 300 $aIncludes bibliographical references and index 311 $a1-119-58576-7 320 $aIncludes bibliographical references and index. 330 $a"The book will review and discuss (with Access and Excel examples) the methods and techniques that investigators can use to uncover anomalies in corporate and public sector data. These anomalies would include errors, biases, duplicates, number rounding, and omissions. The focus will be the detection of fraud, intentional errors, and unintentional errors using data analytics. Despite the quantitative and computing bias, the book will still be interesting to read with interesting vignettes and illustrations. Most chapters will be understandable by accountants and auditors that usually are lacking in the rigors of mathematics and statistics. The data interrogation methods are based on (a) known statistical techniques, and (b) the author's own published research in the field. New to this edition are: Updates to Windows and Microsoft Office R, which is now a viable data analytics product. New fraud cases There are many published books on data mining, which is defined as the analysis of (large) data sets to find unsuspected relationships, and to summarize the data in novel ways that are both understandable and useful to the data owner. The results of such analyses could be sales predictions or discovering previously unknown patterns and rules. Data mining involves using the data for some specific purpose (often tied to marketing) but typically has no fraud detection motive. Yet, data mining can be a valuable tool to detect errors and anomalies that can lead to the discovery of fraud"--$cProvided by publisher. 410 0$aWiley corporate F & A series. 606 $aForensic accounting 615 0$aForensic accounting. 676 $a363.25963 686 $a336.97$2njb/09 686 $a363.25963$2njb/09 700 $aNigrini$b Mark J$g(Mark John),$0970207 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910794161603321 996 $aForensic analytics$92290281 997 $aUNINA