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Fraud and fraud detection : a data analytics approach /
This book takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, New Jersey :
John Wiley & Sons, Inc.,
[2015]
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Gee, Sunder, |e author. | |
| 245 | 1 | 0 | |a Fraud and fraud detection : |b a data analytics approach / |c Sunder Gee. |
| 264 | 1 | |a Hoboken, New Jersey : |b John Wiley & Sons, Inc., |c [2015] | |
| 264 | 4 | |c ©2015 | |
| 300 | |a 1 online resource (xv, 336 pages) : |b color illustrations, charts | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a This book takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. You will learn to: understand the different areas of fraud and their specific detection methods; identify anomalies and risk areas using computerized techniques; develop a step-by-step plan for detecting fraud through data analytics; utilize IDEA software to automate detection and identification procedures. The delineation of detection techniques for each type of fraud makes this book a must-have for students and new fraud prevention professionals, and the step-by-step guidance to automation and complex analytics will prove useful for even experienced examiners. -- |c Edited summary from book. | ||
| 588 | 0 | |a Online resource (Wiley, Bloomberg Law, viewed March 12, 2018). | |
| 505 | 0 | |a Fraud and Fraud Detection; Contents; Foreword; Preface; Acknowledgments; Chapter 1: Introduction; Defining Fraud; Anomalies versus Fraud; Types of Fraud; Assess the Risk of Fraud; Conclusion; Notes; Chapter 2: Fraud Detection; Recognizing Fraud; Data Mining versus Data Analysis and Analytics; Data Analytical Software; Anomalies versus Fraud within Data; Fraudulent Data Inclusions and Deletions; Conclusion; Notes; Chapter 3: The Data Analysis Cycle; Evaluation and Analysis; Software and Technology; Audit and Investigative; Obtaining Data Files; Audit Objectives | |
| 505 | 8 | |a Determine Whether IDEA Is AppropriateData Requirements; Performing the Audit; Obtain Test Files; IDEA Import; After Import; Cleaning Up the Data; Documenting the Results; File Format Types; Preparation for Data Analysis; Data Familiarization; Arranging and Organizing Data; Conclusion; Notes; Chapter 4: Statistics and Sampling; Descriptive Statistics; Inferential Statistics; Measures of Center; Measure of Dispersion; Measure of Variability; Deviations from the Mean; The Mean Deviation; The Variance; The Standard Deviation; Sampling; Statistical Sampling; Nonstatistical Sampling; Sampling Risk | |
| 505 | 8 | |a Benford's Law TestsRelative Size Factor Test; Z-Score; Even Dollar Amounts; Same-Same-Same Test; Same-Same-Different Test; Payments without Purchase Orders Test; Length of Time between Invoice and Payment Dates Test; Search for Post Office Box; Match Employee Address to Supplier; Duplicate Addresses in Vendor Master; Payments to Vendors Not in Master; Gap Detection of Check Number Sequences; Conclusion; Note; Chapter 9: Check-Tampering Schemes; Electronic Payments Fraud Prevention; Check Tampering; Obtaining Checks; Obtaining an Authorized Signature; The Payee; Concealing the Deed | |
| 505 | 8 | |a Data Analytical TestsOther Analytical Tests; Conclusion; Chapter 10: Payroll Fraud; Data and Data Familiarization; Data Familiarization Steps; Data Analysis; Blank Contents in the Last-Name Field; High Number of Payments; Duplicate Key Detection; Payments on Last Day of the Month; Analyzing Files by Payment Type; Regular Salary Payments; Overtime Wages Payments; Signing Incentive Plan Payments; Comparing Regular Salary Payments with Other Payment Types; The Payroll Register; Payroll Register Tests; Payroll Master and Commission Tests; Conclusion; Notes | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Fraud. | |
| 650 | 0 | |a Managerial accounting. | |
| 650 | 0 | |a Data mining. | |
| 650 | 6 | |a Fraude. | |
| 650 | 6 | |a Comptabilité de gestion. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 7 | |a fraud. |2 aat | |
| 650 | 7 | |a Data mining |2 fast | |
| 650 | 7 | |a Fraud |2 fast | |
| 650 | 7 | |a Managerial accounting |2 fast | |
| 776 | 0 | 8 | |i Print version: |a Gee, Sunder. |t Fraud and fraud detection. |d Hoboken : Wiley, 2014 |z 9781118779675 |w (DLC) 2014022943 |w (OCoLC)881387996 |
| 776 | 0 | 8 | |i Print version: |a Gee, Sunder. |t Fraud and fraud detection : a data analytics approach. |d Hoboken, New Jersey : Wiley, ©2015 |h xv, 336 pages |k Wiley corporate F & A. |z 9781118779651 |
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