How Informative Are Fraud and Non-Fraud Firms\u27 Earnings?

This study evaluates how informative the earnings of fraud firms are compared to peer non-fraud firms by assessing informativeness in the context of persistence, analysts’ forecast errors, and stock returns. There are differences in how informative the earnings of fraud firms are to analysts’ forecasts and returns in the pre-fraud period, but not in the fraud period. In the post- fraud period, there is no difference in how informative fraud firms’ earnings are to analysts’ earnings forecasts. Furthermore, fraud firm’s earnings are not differentially associated with excess returns post-fraud. When earnings are decomposed into accruals and cash flows, fraud firms’ accruals are more persistent pre-fraud and less so post- fraud while cash flows are not differentially persistent conditional on fraud. The study presents insights that can help practitioners, auditors, regulators, and researchers identify fraud candidates

How local media coverage of voter fraud influences partisan perceptions in the United States

Extant findings show that voter fraud is extremely rare and difficult to prove in the United States. Voter’s knowledge about voter fraud allegations likely comes through the media, who tend to sensationalize the issue. In this study, we argue that the more voters are exposed to media coverage of voter fraud allegations, the more likely that they will perceive that voter fraud is a frequent problem. We merge the 2012 Survey of Performance of American Elections with state-level media coverage of voter fraud leading up to the 2012 election. Our results show that media coverage of voter fraud is associated with public beliefs about voter fraud. In states where fraud was more frequently featured in local media outlets, public concerns about voter fraud were heightened. In particular, we find that press attention to voter fraud has a larger influence on Republicans than Democrats and Independents. We further find that media coverage of voter fraud does not further polarize partisan perceptions of voter fraud. Rather, political interest moderates state media coverage on voter fraud beliefs only among Republicans. Lastly, our results provide no support that demographic changes, approval of election administration, or information concerning actual reported voting irregularities have any discernable effects on partisan perceptions

Tax fraud by firms and optimal auditing

Abstract Tax fraud is an issue of increasing importance in China. One particularly signi…cant fraud involves excessive claims for the rebate of VAT on exported goods. This fraud has two interesting features. First, it requires the collusion of an intermediary to supply the false documentation that supports a rebate application. Second, the punishment schedule is convex -with capital punishment used in major fraud cases. These features ensure that the payo¤ function of a …rm engaging in fraud is strictly concave in the level of fraud. This gives a well-de…ned optimization without the need to appeal to risk aversion. We show that the existence of fraud does not a¤ect the real output decision of the …rm nor the tax policy of the government. Audit resources can be used to detect …rms engaged in fraud as well as the intermediaries who supply false documents. Under reasonable assumptions it is shown that resources should be focused on detecting …rms and not intermediaries. Finally, if the government must take action on fraud a convex punishment scheme is shown to be optimal

An analysis of Voter Fraud in The United States

As federal and state officials consider future reform efforts, as well as the merits of existing reforms, there is an acute need for better information and analysis about election and voter fraud issues. While the issue of fraud is raised continually in discussions of election reform, to date there have been few major studies of voter fraud in the United States. Too often in this area, hearsay and anecdotal information are put forth as fact in important public policy debates. Many key questions about fraud remain unanswered, including: How often does voter fraud occur? How serious a problem is fraud compared to other problems with the election process, such as those that occurred in Florida in the 2000 election or in Ohio in 2004? What kinds of voting methods are most vulnerable to corruption? What administrative, technological and legal steps can be taken to reduce the chances of voter fraud while also expanding opportunities to register and vote

Does Canada Have a Problem with Occupational Fraud?

Small and medium-sized enterprises (SMEs) are an important collective force in the Canadian economy, however the visibility and economic power of small businesses suffer due to their size and frequent turnover. When it comes to the issue of businesses being subject to occupational fraud, the moderate visibility of SMEs only contributes to the challenge of assessing the real scope of the problem. This paper seeks to examine the prevalence and types of occupational fraud experienced by Canadian SMEs as well as gathers information on prevention and detection methods used to safeguard against occupational fraud. That is done based on data compiled from a survey of 802 SMEs across Canada. The analysis shows that a substantial proportion of SMEs experience incidents of occupational fraud; however, the majority of SMEs are not fully prepared to respond to fraud. Furthermore, SMEs’ experience with and attitudes toward fraud vary noticeably with company characteristics, although a large proportion of SMEs believe risk to occupational fraud is low.Occupational fraud, fraud prevention, fraud detection, types of occupational fraud, Canadian small and medium businesses, employee fraud, internal fraud

Can the general fraud offence 'get the law right'? Some perspectives on the 'problem' of financial crime

The Fraud Bill, which received Royal Assent on 8 November 2006, created an offence of fraud in English criminal law which marks a departure of utmost significance from the approach adopted hitherto, whereby a number of related offences cover behaviour deemed to amount to fraud. To mark the passage of the Fraud Act 2006 into law, this article examines the references which were made during its consideration in Parliament to fraud as activity which is serious and which is often erroneously portrayed as 'victimless' crime. In joining these key criminal policy-making debates with academic study of white-collar crime, it will be suggested that as yet too little attention is being paid to 'ambiguous' popular perceptions of financial crimes for there to be confidence that the fraud offence will, in the words of the current Solicitor-General, 'get the law right'

Search Rank Fraud De-Anonymization in Online Systems

We introduce the fraud de-anonymization problem, that goes beyond fraud detection, to unmask the human masterminds responsible for posting search rank fraud in online systems. We collect and study search rank fraud data from Upwork, and survey the capabilities and behaviors of 58 search rank fraudsters recruited from 6 crowdsourcing sites. We propose Dolos, a fraud de-anonymization system that leverages traits and behaviors extracted from these studies, to attribute detected fraud to crowdsourcing site fraudsters, thus to real identities and bank accounts. We introduce MCDense, a min-cut dense component detection algorithm to uncover groups of user accounts controlled by different fraudsters, and leverage stylometry and deep learning to attribute them to crowdsourcing site profiles. Dolos correctly identified the owners of 95% of fraudster-controlled communities, and uncovered fraudsters who promoted as many as 97.5% of fraud apps we collected from Google Play. When evaluated on 13,087 apps (820,760 reviews), which we monitored over more than 6 months, Dolos identified 1,056 apps with suspicious reviewer groups. We report orthogonal evidence of their fraud, including fraud duplicates and fraud re-posts.Comment: The 29Th ACM Conference on Hypertext and Social Media, July 201

A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries. The failure of internal auditing system of the organization in identifying the accounting frauds has lead to use of specialized procedures to detect financial accounting fraud, collective known as forensic accounting. Data mining techniques are providing great aid in financial accounting fraud detection, since dealing with the large data volumes and complexities of financial data are big challenges for forensic accounting. This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques based accounting fraud detection. The systematic and comprehensive literature review of the data mining techniques applicable to financial accounting fraud detection may provide a foundation to future research in this field. The findings of this review show that data mining techniques like logistic models, neural networks, Bayesian belief network, and decision trees have been applied most extensively to provide primary solutions to the problems inherent in the detection and classification of fraudulent data.Comment: 11 Pages. International Journal of Computer Applications February 201