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.

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.

Praise for Computer-Aided Fraud Prevention and Detection: A Step-by-Step Guide "A wonderful desktop reference for anyone trying to move from traditional auditing to integrated auditing. The numerous case studies make it easy to understand and provide a how-to for those?seeking to implement automated tools including continuous assurance. Whether you are just starting down the path or well on your way, it is a valuable resource." -Kate M. Head, CPA, CFE, CISA Associate Director, Audit and Compliance University of South Florida "I have been fortunate enough to learn from Dave's work over the last fifteen years, and this publication is no exception. Using his twenty-plus years of experience, Dave walks through every aspect of detecting fraud with a computer from the genesis of the act to the mining of data for its traces and its ultimate detection. A complete text that first explains how one prevents and detects fraud regardless of technology and then shows how by automating such procedures, the examiners' powers become superhuman." -Richard B. Lanza, President, Cash Recovery Partners, LLC "Computer-Aided Fraud Prevention and Detection: A Step-by-Step Guide helps management and auditors answer T. S. Eliot's timeless question, 'Where is the knowledge lost in information?' Data analysis provides a means to mine the knowledge hidden in our information. Dave Coderre has long been a leader in educating auditors and others about Computer Assisted Audit Techniques. The book combines practical approaches with unique data analysis case examples that compel the readers to try the techniques themselves." -Courtenay Thompson Jr. Consultant, Courtenay Thompson & Associates

Practical examples, sample reports, best practices and recommendations to help you deter, detect, and prevent financial statement fraud Financial statement fraud (FSF) continues to be a major challenge for organizations worldwide. Financial Statement Fraud: Prevention and Detection, Second Edition is a superior reference providing you with an up-to-date understanding of financial statement fraud, including its deterrence, prevention, and early detection. You will find A clear description of roles and responsibilities of all those involved in corporate governance and the financial reporting process to improve the quality, reliability and transparency of financial information. Sample reports, examples, and documents that promote a real-world understanding of incentives, opportunities, and rationalizations Emerging corporate governance reforms in the post-SOX era, including provisions of the SOX Act, global regulations and best practices, ethical considerations, and corporate governance principles Practical examples and real-world "how did this happen" discussions that provide valuable insight for corporate directors and executives, auditors, managers, supervisory personnel and other professionals saddled with anti-fraud responsibilities Expert advice from the author of Corporate Governance and Ethics and coauthor of the forthcoming Wiley textbook, White Collar Crime, Fraud Examination and Financial Forensics Financial Statement Fraud, Second Edition contains recommendations from the SEC Advisory Committee to reduce the complexity of the financial reporting process and improving the quality of financial reports.

Step-by-step guidance for board members and executives on preventing and detecting accounting fraud In the wake of highly publicized allegations of accounting irregularities and fraudulent financial reporting that are shaking up today's corporate community, Financial Fraud Prevention and Detection provides a step-by-step guide to how these crises can envelop a company and how to prevent them from happening in the first place. It is written for almost everyone involved: outside directors, audit committee members, senior executives, CFOs, CPAs, in-house lawyers, and outside law firms. Provides a blueprint for Fraud Prevention and Detection for corporate executives Presents step-by-step guidance to corporate boards and C-suite executives on managing the threat of accounting fraud Prepares directors and executives for the possibility of accounting irregularities Answers the question of how accounting fraud starts—and grows With solid strategies for prevention of accounting fraud as well as a process to follow when fraud has been discovered, Financial Fraud Prevention and Detection vividly explores the corporate environment that causes fraud, how it spreads, the kind of crises it can create for a company, and the best ways to deal with it.

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.

Lessons can be learned from major fraud cases. Whether the victim is a company, public agency, nonprofit, foundation, or charity, there is a high likelihood that many of these frauds could have been prevented or detected sooner if early Red Flag warning signs had been identified and acted upon. Fraud Prevention and Detection: Warning Signs and the