Identifying Fraud An In Depth Guide
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques
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.
Computer-aided Fraud Prevention and Detection
Using software to detect improper transactions are techniques that have grown in importance for fraud examiners. This book provides fraud examiners and auditors with step-by-step guidance on using data extraction and software to detect and prevent fraud. Its implementation guidance is supplemented by more than 60 case studies. Plus, it enables readers to use data to identify known and unknown symptoms of fraud. Auditors and fraud examiners will discover how to leverage data analysis as a powerful tool to detect and prevent fraud from occurring in any organization.
The Complete Guide to Spotting Accounting Fraud & Cover-ups
Author: Martha Maeda
language: en
Publisher: Atlantic Publishing Company
Release Date: 2010
In 2009, high-profile fraud cases like the Ponzi schemes of Bernard Madoff and Arthur Nadel vividly illustrated the harm done to investors who placed their trust in these apparently successful money managers and then discovered their money had never been invested at all. News stories featured 90-year-olds forced by necessity to work in supermarkets, elderly people losing their homes because their life savings were gone, and wealthy retirees suddenly unable to pay their electricity bills. Charities were forced to curtail their services, lay off staff, and even close their doors forever as their funds evaporated. Almost every day, there are stories in the media about dishonest employees who have robbed their organisations of hundreds of thousands of dollars. Not so well-publicised are the countless smaller thefts occurring every day from cash registers, warehouses, and business bank accounts. Sadly, the organisations that have the most to lose small businesses, family-run companies, churches, and charities are often the most vulnerable because of their size and inexperience. According to the Association of Certified Fraud Examiners, accounting fraud cost over $994 billion in 2008, and the average organisation lost 7 percent of its total revenue to fraud. How can you prevent this from happening to you as an investor, business owner, or a person attempting to acquire or merge with another firm? Read this book and you will be able to understand, detect, and avoid accounting fraud. You will learn how to identify fraud, how to spot minor abnormalities that may hide fraud, how to spot forgeries, and how to prove your case, as well as what to immediately suspect and methods for uncovering scams. You will know what signs to look for, including excessive turnover of lawyers and auditors, changing professionals in the middle of a transaction, inconsistent information, and significant declines in stock prices. In addition, you will know how to recognise the common manoeuvres, earnings manipulation, premature and fictitious revenue, overvalued assets, undervalued liabilities, bogus revenue, expenses that have been shifted to another period, overstating revenues, understating expenses, and the misuse and misdirecting of funds. This new book is filled with studies and discussions of fraud cases and how they could have been avoided, checklists for detecting accounts misdeeds, and advice from analysts, CFOs, and CPAs. This manual will be an indispensable aid for serious investors, industry pros, acquisition and merger managers, and small business owners alike. After reading this book you will no longer have to worry about accounting fraud and you can increase your company's profits.