Author: Leonard W. Vona Publisher: John Wiley & Sons ISBN: 111918679X Category : Business & Economics Languages : en Pages : 400
Book Description
Uncover hidden fraud and red flags using efficient data analytics Fraud Data Analytics Methodology addresses the need for clear, reliable fraud detection with a solid framework for a robust data analytic plan. By combining fraud risk assessment and fraud data analytics, you'll be able to better identify and respond to the risk of fraud in your audits. Proven techniques help you identify signs of fraud hidden deep within company databases, and strategic guidance demonstrates how to build data interrogation search routines into your fraud risk assessment to locate red flags and fraudulent transactions. These methodologies require no advanced software skills, and are easily implemented and integrated into any existing audit program. Professional standards now require all audits to include data analytics, and this informative guide shows you how to leverage this critical tool for recognizing fraud in today's core business systems. Fraud cannot be detected through audit unless the sample contains a fraudulent transaction. This book explores methodologies that allow you to locate transactions that should undergo audit testing. Locate hidden signs of fraud Build a holistic fraud data analytic plan Identify red flags that lead to fraudulent transactions Build efficient data interrogation into your audit plan Incorporating data analytics into your audit program is not about reinventing the wheel. A good auditor must make use of every tool available, and recent advances in analytics have made it accessible to everyone, at any level of IT proficiency. When the old methods are no longer sufficient, new tools are often the boost that brings exceptional results. Fraud Data Analytics Methodology gets you up to speed, with a brand new tool box for fraud detection.
Author: Bart Baesens Publisher: John Wiley & Sons ISBN: 1119146836 Category : Computers Languages : en Pages : 406
Book Description
Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.
Author: Sunder Gee Publisher: John Wiley & Sons ISBN: 1118779657 Category : Business & Economics Languages : en Pages : 358
Book Description
Detect fraud faster—no matter how well hidden—with IDEA automation Fraud and Fraud Detection takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book. Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but Fraud and Fraud Detection helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers 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. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. Fraud and Fraud Detection is a guide to more efficient, more effective fraud identification.
Author: Delena D. Spann Publisher: John Wiley & Sons ISBN: 1118282736 Category : Business & Economics Languages : en Pages : 176
Book Description
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.
Author: Sunder Gee Publisher: ISBN: Category : Data mining Languages : en Pages : 352
Book Description
Detect fraud faster--no matter how well hidden--with IDEA automation Fraud and Fraud Detection takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book. Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but Fraud and Fraud Detection helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers 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. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. Fraud and Fraud Detection is a guide to more efficient, more effective fraud identification.
Author: Jean Paul Isson Publisher: John Wiley & Sons ISBN: 1119129753 Category : Computers Languages : en Pages : 432
Book Description
Turn unstructured data into valuable business insight Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices. Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work. Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence. You will learn: How to increase Customer Acquisition and Customer Retention with UDA The Power of UDA for Fraud Detection and Prevention The Power of UDA in Human Capital Management & Human Resource The Power of UDA in Health Care and Medical Research The Power of UDA in National Security The Power of UDA in Legal Services The Power of UDA for product development The Power of UDA in Sports The future of UDA From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis.
Author: Sunder Gee Publisher: Wiley ISBN: 9781118936764 Category : Data mining Languages : en Pages : 0
Book Description
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. --
Author: Gerard Blokdyk Publisher: Createspace Independent Publishing Platform ISBN: 9781979909075 Category : Languages : en Pages : 134
Book Description
What potential environmental factors impact the Data analysis techniques for fraud detection effort? What key business process output measure(s) does Data analysis techniques for fraud detection leverage and how? Who sets the Data analysis techniques for fraud detection standards? Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Data analysis techniques for fraud detection? Among the Data analysis techniques for fraud detection product and service cost to be estimated, which is considered hardest to estimate? This easy Data analysis techniques for fraud detection self-assessment will make you the dependable Data analysis techniques for fraud detection domain specialist by revealing just what you need to know to be fluent and ready for any Data analysis techniques for fraud detection challenge. How do I reduce the effort in the Data analysis techniques for fraud detection work to be done to get problems solved? How can I ensure that plans of action include every Data analysis techniques for fraud detection task and that every Data analysis techniques for fraud detection outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data analysis techniques for fraud detection opportunity costs are low? How can I deliver tailored Data analysis techniques for fraud detection advise instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data analysis techniques for fraud detection essentials are covered, from every angle: the Data analysis techniques for fraud detection self-assessment shows succinctly and clearly that what needs to be clarified to organize the business/project activities and processes so that Data analysis techniques for fraud detection outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data analysis techniques for fraud detection practitioners. Their mastery, combined with the uncommon elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data analysis techniques for fraud detection are maximized with professional results. Your purchase includes access details to the Data analysis techniques for fraud detection self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Author: Gerardus Blokdyk Publisher: Createspace Independent Publishing Platform ISBN: 9781983813047 Category : Languages : en Pages : 134
Book Description
What potential environmental factors impact the Data analysis techniques for fraud detection effort? What key business process output measure(s) does Data analysis techniques for fraud detection leverage and how? Who sets the Data analysis techniques for fraud detection standards? Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Data analysis techniques for fraud detection? Among the Data analysis techniques for fraud detection product and service cost to be estimated, which is considered hardest to estimate? This easy Data analysis techniques for fraud detection self-assessment will make you the dependable Data analysis techniques for fraud detection domain specialist by revealing just what you need to know to be fluent and ready for any Data analysis techniques for fraud detection challenge. How do I reduce the effort in the Data analysis techniques for fraud detection work to be done to get problems solved? How can I ensure that plans of action include every Data analysis techniques for fraud detection task and that every Data analysis techniques for fraud detection outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data analysis techniques for fraud detection opportunity costs are low? How can I deliver tailored Data analysis techniques for fraud detection advise instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data analysis techniques for fraud detection essentials are covered, from every angle: the Data analysis techniques for fraud detection self-assessment shows succinctly and clearly that what needs to be clarified to organize the business/project activities and processes so that Data analysis techniques for fraud detection outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data analysis techniques for fraud detection practitioners. Their mastery, combined with the uncommon elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data analysis techniques for fraud detection are maximized with professional results. Your purchase includes access details to the Data analysis techniques for fraud detection self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Author: Leonard W. Vona
Author: Bart Baesens
Author: Sunder Gee
Author: Delena D. Spann
Author: Sunder Gee
Author: Jean Paul Isson
Author: Sunder Gee
Author: David G. Coderre
Author: Gerard Blokdyk
Author: Gerardus Blokdyk