Computer Aided Fraud Prevention And Detection

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

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 Red Flag System will enable officers and directors, internal and external stakeholders, as well as outside analysts to protect themselves and their organizations against fraud by effectively detecting, analyzing, and acting on early Red Flag warning signs. Based on an empirically tested strategy, the Red Flag System reflects the authors’ more than 100 years combined experience in the investigation of fraud in high-profile, global cases in North America, Africa, Europe, and the Far East. Readers of this book will: Acquire a general awareness of the nature, characteristics, and dynamics of fraud Understand the process for determining whether a fraud has been committed Develop an understanding of enterprise risk management approaches for fraud risk management, compliance risk management, and managing the risk of fraudulent financial reporting—including an understanding of the limitations inherent in these approaches Learn how to find Red Flag indicators of fraud or suspicious transactions in financial statements, budgets, and contracts Know how to ensure that, once a Red Flag has been identified, appropriate action is taken Fraud can lead to significant financial loss as well as bad press and publicity with significant reputational impact for officers, directors, corporations, and their stakeholders. This book’s no-nonsense approach empowers those charged with protecting organizations to stop these frauds before the organization’s livelihood is jeopardized or to mitigate damage when fraud has occurred.

Detect fraud faster—no matter how well hidden—withIDEA automation Fraud and Fraud Detection takes an advanced approach tofraud management, providing step-by-step guidance on automatingdetection and forensics using CaseWare's IDEA software. The bookbegins by reviewing the major types of fraud, then details thespecific computerized tests that can detect them. Readers willlearn to use complex data analysis techniques, including automationscripts, allowing easier and more sensitive detection of anomaliesthat require further review. The companion website provides accessto a demo version of IDEA, along with sample scripts that allowreaders to immediately test the procedures from the book. Business systems' electronic databases have grown tremendouslywith the rise of big data, and will continue to increase atsignificant rates. Fraudulent transactions are easily hidden inthese enormous datasets, but Fraud and Fraud Detection helpsreaders gain the data analytics skills that can bring theseanomalies to light. Step-by-step instruction and practical adviceprovide the specific abilities that will enhance the audit andinvestigation process. Readers will learn to: Understand the different areas of fraud and their specificdetection methods Identify anomalies and risk areas using computerizedtechniques Develop a step-by-step plan for detecting fraud through dataanalytics Utilize IDEA software to automate detection and identificationprocedures The delineation of detection techniques for each type of fraudmakes this book a must-have for students and new fraud preventionprofessionals, and the step-by-step guidance to automation andcomplex analytics will prove useful for even experienced examiners.With datasets growing exponentially, increasing both the speed andsensitivity of detection helps fraud professionals stay ahead ofthe game. Fraud and Fraud Detection is a guide to moreefficient, more effective fraud identification.

FRAUD AUDITING AND FORENSIC ACCOUNTING With the responsibility of detecting and preventing fraud falling heavily on the accounting profession, every accountant needs to recognize fraud and learn the tools and strategies necessary to catch it in time. Providing valuable information to those responsible for dealing with prevention and discovery of financial deception, Fraud Auditing and Forensic Accounting, Fourth Edition helps accountants develop an investigative eye toward both internal and external fraud and provides tips for coping with fraud when it is found to have occurred. Completely updated and revised, the new edition presents: Brand-new chapters devoted to fraud response as well as to the physiological aspects of the fraudster A closer look at how forensic accountants get their job done More about Computer-Assisted Audit Tools (CAATs) and digital forensics Technological aspects of fraud auditing and forensic accounting Extended discussion on fraud schemes Case studies demonstrating industry-tested methods for dealing with fraud, all drawn from a wide variety of actual incidents Inside this book, you will find step-by-step keys to fraud investigation and the most current methods for dealing with financial fraud within your organization. Written by recognized experts in the field of white-collar crime, this Fourth Edition provides you, whether you are a beginning forensic accountant or an experienced investigator, with industry-tested methods for detecting, investigating, and preventing financial schemes.

This book discusses various common occupational and organizational fraud schemes, based on the Association of Certified Fraud Examiners (ACFE) fraud tree and assist fraud examiners and auditors in correctly choosing the appropriate audit tests to uncover such various fraud schemes. The book also includes information about audit test red flags to watch out for, a list of recommended controls to help prevent future fraud related incidents, as well as step-by-step demonstrations of a number of common audit tests using IDEA® as a CAATT tool.

The prediction of the valuation of the “quality” of firm accounting disclosure is an emerging economic problem that has not been adequately analyzed in the relevant economic literature. While there are a plethora of machine learning methods and algorithms that have been implemented in recent years in the field of economics that aim at creating predictive models for detecting business failure, only a small amount of literature is provided towards the prediction of the “actual” financial performance of the business activity. Machine Learning Applications for Accounting Disclosure and Fraud Detection is a crucial reference work that uses machine learning techniques in accounting disclosure and identifies methodological aspects revealing the deployment of fraudulent behavior and fraud detection in the corporate environment. The book applies machine learning models to identify “quality” characteristics in corporate accounting disclosure, proposing specific tools for detecting core business fraud characteristics. Covering topics that include data mining; fraud governance, detection, and prevention; and internal auditing, this book is essential for accountants, auditors, managers, fraud detection experts, forensic accountants, financial accountants, IT specialists, corporate finance experts, business analysts, academicians, researchers, and students.

This book constitutes the refereed proceedings of the 18th International Conference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes papers presented at the 6th Mining Humanistic Data Workshop (MHDW 2017) and the 2nd Workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE).