Practical Approach To Prevention And Detection Of Fraud
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Practical Approach to Prevention and Detection of Fraud
Author: CK Cho, Barrister LLB (Hons.) London CFE
language: en
Publisher: SouthEastern Publushers
Release Date: 2012-11-06
This Guide Book was written to help you to: - Consider various international best practices for internal control and fraud risk management; - Outline the legal elements of fraud offences such as Theft, Deception, Fraud and Conspiracy to Defraud; - Explain the law, evidence and procedures relating to the prevention, detection and investigation of fraud; - Consider the practical and legal issues in conducting an independent internal investigation into fraudulent activities at the workplace; - Apply basic investigative skills such as interview techniques; - Set out the essential steps of a fraud investigation, including collection and preservation of evidence. The Guide is prepared by respected professionals with extensive experience practicing and teaching fraud investigation and internal control. While the Guide is based on current Hong Kong law, it can be a useful reference book for anyone with a professional interest in fraud prevention and detection.
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.
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.