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These hearing transcripts present testimony on the high risks and emerging fraud in several areas of the federal government, including the Student Loan Program of the Education Department (ED), the Multifamily Housing Program of the Department of Housing and Urban Development (HUD), and Internal Revenue Service (IRS) tax return filing. Testimony was heard from concerned senators and government officials responsible for risk management and fraud in these departments and agencies. Current and possible solutions to risk management and fraud were discussed. Opening and/or prepared statements were given by: Senators John Glenn, Byron L. Dorgan, Jim Sasser, William S. Cohen, and William V. Roth, Jr. Testimony was heard from: (1) the special assistant to the comptroller general and the director of tax systems issues, General Accounting Office (GAO); (2) the commissioner, deputy commissioner, and other officials of the IRS; (3) the deputy secretary, inspector general, and other officials of ED; and (4) the inspector general, assistant inspector general for audit, and other officials of HUD. An appendix contains the prepared statements of several witnesses, along with written questions and answers from officials of GAO, ED, HUD, and the Department of Treasury. (MDM)
A Short Guide to Fraud Risk is for: * anyone who needs to better understand fraud risks, either company-wide, or in a specific business unit; * directors and managers who would like to add value by building fraud resistance into their organization and to demonstrate to shareholders, regulators or other stakeholders that they are managing fraud risks, rather than just reacting to incidents; * regulators, auditors and compliance professionals who need to assess the effectiveness of an organisation's fraud prevention measures. The book gives a concise but thorough introduction to the risk of fraud based on a six-element strategy. It includes practical steps to assess and treat fraud risks across an organisation, including those relating to executive directors. It also provides practical steps to develop fraud awareness across an organisation and how to implement an effective fraud detection and incident management program. The application of the principles is illustrated with example documents and numerous case studies aimed at assisting the reader to implement either individual elements or a complete fraud risk management strategy.
Fraud has become a challenging phenomena affecting economies worldwide. Anti-fraud measures are an integral part of today’s management practices and have found their way into business education. Yet in developing countries these topics have long been neglected and only limited research has been conducted in this area. This book fills an essential gap by analyzing the impact of fraud on developing economies, describing successful anti-fraud methods and featuring cases that exemplify the measures described. The book features contributions by outstanding experts in the field and is intended for academic readers with a special interest in fraud research.
Policymakers and program managers are continually seeking ways to improve accountability in achieving an entity's mission. A key factor in improving accountability in achieving an entity's mission is to implement an effective internal control system. An effective internal control system helps an entity adapt to shifting environments, evolving demands, changing risks, and new priorities. As programs change and entities strive to improve operational processes and implement new technology, management continually evaluates its internal control system so that it is effective and updated when necessary. Section 3512 (c) and (d) of Title 31 of the United States Code (commonly known as the Federal Managers? Financial Integrity Act (FMFIA)) requires the Comptroller General to issue standards for internal control in the federal government.
This book provides a user-friendly guide to current and emerging issues in fraud both internal to the company, and external. It explains the terminology used and sets out the chief risks which management accountants need to be aware of. It then sets out a practical framework for the management and mitigation of fraud risk. This is followed up by an explanation of what to do in the event of concerns that a fraud has been perpetrated, is underway or is being attempted. The book also guides the reader through the process of dealing with the law enforcement authorities in the event of an investigation. The book is for all those accountants who are not professionals in risk management or investigation procedures, but who need to be aware of the issues, many of which will impact on their area of responsibility; it therefore aims to give them a user-friendly manual to the issue of fraud risk. In addition the book will provide a valuable update on emerging trends in the fraud environment. The author is a financial services and regulatory consultant with extensive experience in fraud risk management. She is also Manager, Corporate Governance for an international life company, and an examiner and moderator who lectures and writes extensively on a wide range of compliance and financial services matters. The book is in three sections: Section 1: What is fraud? What are the emerging trends in fraud at present? Section 2: what risks may you encounter in your business, and what fraud management systems should you have in place? Section 3: post-event fraud management ? what to do when your concerns are aroused that a fraud has taken place or is being attempted? * makes accountants aware of different types of fraud risk * explains practical issues including post-fraud event management * The author, a financial and regulatory consultant, offers her extensive experience in fraud risk management
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.
An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.
Protect your organisation by looking at it through a new lens to spot the early warning signs of fraud.
An in-depth scrutiny into the American savings and loan financial crisis in the 1980s. The authors come to conclusions about the deliberate nature of this financial fraud and the leniency of the criminal justice system on these 'Gucci-clad white-collar criminals'.