Fraud Analytics - Strategies and Methods for Detection and Prevention (Hardcover)

Proven guidance for expertly using analytics in fraud examinations, financial analysis, auditing and fraud prevention Fraud Analytics thoroughly reveals the elements of analysis that are used in today's fraud examinations, fraud investigations, and financial crime investigations. This valuable resource reviews the types of analysis that should be considered prior to beginning an investigation and explains how to optimally use data mining techniques to detect fraud. Packed with examples and sample cases illustrating pertinent concepts in practice, this book also explores the two major data analytics providers: ACL and IDEA. * Looks at elements of analysis used in today's fraud examinations * Reveals how to use data mining (fraud analytic) techniques to detect fraud * Examines ACL and IDEA as indispensable tools for fraud detection * Includes an abundance of sample cases and examples Written by Delena D Spann, Board of Regent (Emeritus) for the Association of Certified Fraud Examiners (ACFE), who currently serves as Advisory Board Member of the Association of Certified Fraud Examiners, Board Member of the Education Task Force of the Association of Certified Anti-Money Laundering Specialists ASIS International (Economic Crime Council) and Advisory Board Member of the Robert Morris University (School of Business), Fraud Analytics equips you with authoritative fraud analysis techniques you can put to use right away.

General

Imprint:	John Wiley & Sons
Country of origin:	United States
Release date:	November 2013
First published:	October 2013
Authors:	D Spann
Dimensions:	232 x 158 x 18mm (L x W x T)
Format:	Hardcover
Pages:	176
ISBN-13:	978-1-118-23068-8
Categories:	Books > Business & Economics > Finance & accounting > General Books > Social sciences > Sociology, social studies > Crime & criminology > General Books > Business & Economics > Business & management > Management of specific areas > Budgeting & financial management Promotions
LSN:	1-118-23068-X
Barcode:	9781118230688

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