Mapping the American Shareholder Litigation Experience: A Survey of Empirical Studies of the Enforcement of the U.S. Securities Law

In this paper, we provide an overview of the most significant empirical research that has been conducted in recent years on the public and private enforcement of the federal securities laws. The existing studies of the U.S. enforcement system provide a rich tapestry for assessing the value of enforcement, both private and public, as well as market penalties for fraudulent financial reporting practices. The relevance of the U.S. experience is made broader by the introduction through the PSLRA in late 1995 of new procedures for the conduct of private suits and the numerous efforts to evaluate the effects of those provisions. We believe that the evidence reviewed here shows that the PSLRA\u27s provisions have largely achieved their intended purposes. For example, many more private suits are headed by an institutional lead plaintiff, such plaintiffs appear to fulfill the desired role of monitoring the suit\u27s prosecution and their presence is associated with suits yielding better settlements and lower attorneys\u27 fees awards. SEC enforcement efforts, while significant, have tended to focus on weaker targets, suggesting that the big fish get away. Equally importantly, markets impose their own discipline on companies whose managers release false financial reports and, in turn, firms discipline the managers who are responsible for false misleading reporting, perhaps because of the presence of, or potential for, private enforcement actions

Mapping the American Shareholder Litigation Experience: A Survey of Empirical Studies of the Enforcement of the U.S. Securities Law

In this paper, we provide an overview of the most significant empirical research that has been conducted in recent years on the public and private enforcement of the federal securities laws. The existing studies of the U.S. enforcement system provide a rich tapestry for assessing the value of enforcement, both private and public, as well as market penalties for fraudulent financial reporting practices. The relevance of the U.S. experience is made broader by the introduction through the PSLRA in late 1995 of new procedures for the conduct of private suits and the numerous efforts to evaluate the effects of those provisions. We believe that the evidence reviewed here shows that the PSLRA\u27s provisions have largely achieved their intended purposes. For example, many more private suits are headed by an institutional lead plaintiff, such plaintiffs appear to fulfill the desired role of monitoring the suit\u27s prosecution and their presence is associated with suits yielding better settlements and lower attorneys\u27 fees awards. SEC enforcement efforts, while significant, have tended to focus on weaker targets, suggesting that the big fish get away. Equally importantly, markets impose their own discipline on companies whose managers release false financial reports and, in turn, firms discipline the managers who are responsible for false misleading reporting, perhaps because of the presence of, or potential for, private enforcement actions

Tool to Detect Spam Websites

Traveling is about relaxing and not worrying about being scammed and losing money. The Internet is a wide place that is changing every day. Having a guide to navigate unknown places goes a long way to staying safe. In this paper, I have used several identifiers and provided analysis on the effectiveness of these identifiers. Travel Website fraud is a severe problem which is widespread around the world. Studies of travel scams are mainly focused on finding different ways that attacker’s targets on the innocent travelers. Now the technology is advanced and that is causing newer and newer techniques to scam people. By illustrating the techniques to find such frauds and to prevent people from getting scammed is something this paper is trying to achieve. In this paper we will look at the various problems and preventive measures that need to be taken while browsing the internet. In this paper I will be talking about the tools I have used for analyzing a website. I will also be providing the analysis of the different identifiers in finding out if a website is fake or genuine. The results and the conclusions from the analysis can then be used in designing a safe tool which can be used for keeping the internet users safer and wiser. The safe rules can be used to develop browser addons, computer applications etc

Address to Joint Meeting of Houston Chapter, Texas Society of Certified Public Accounants and Houston Chapter, Fianncial Executives Institute, Houston, Texas, November 18, 1986: a pre-exposure of the Commission\u27s exposure draft

https://egrove.olemiss.edu/aicpa_assoc/1500/thumbnail.jp

Systematic Literature Review

Mutemi, A., & Bação, F. (2023). E-Commerce Fraud Detection Based on Machine Learning Techniques: Systematic Literature Review. Big Data Mining and Analytics, 1-27. https://doi.org/10.26599/BDMA.2023.9020023The e-commerce industry's rapid growth, accelerated by the COVID-19 pandemic, has led to an alarming increase in digital fraud and associated losses. To establish a healthy e-commerce ecosystem, robust cyber security and anti-fraud measures are crucial. However, research on fraud detection systems has struggled to keep pace due to limited real-world datasets. Advances in artificial intelligence, machine learning, and cloud computing have revitalized research and applications in this domain. While machine learning and data mining techniques are popular in fraud detection, specific reviews focusing on their application in ecommerce platforms like eBay and Facebook are lacking depth. Existing reviews provide broad overviews but fail to grasp the intricacies of machine learning algorithms in the e-commerce context. To bridge this gap, our study conducts a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) methodology. We aim to explore the effectiveness of these techniques in fraud detection within digital marketplaces and the broader e-commerce landscape. Understanding the current state of the literature and emerging trends is crucial given the rising fraud incidents and associated costs. Through our investigation, we identify research opportunities and provide insights to industry stakeholders on key machine learning and data mining techniques for combating e-commerce fraud. Our paper examines the research on these techniques as published in the past decade. Employing the PRISMA approach, we conducted a content analysis of 101 publications, identifying research gaps, recent techniques, and highlighting the increasing utilization of artificial neural networks in fraud detection within the industry.publishersversionepub_ahead_of_prin

Credit Card Fraud Detection Using Asexual Reproduction Optimization

As the number of credit card users has increased, detecting fraud in this domain has become a vital issue. Previous literature has applied various supervised and unsupervised machine learning methods to find an effective fraud detection system. However, some of these methods require an enormous amount of time to achieve reasonable accuracy. In this paper, an Asexual Reproduction Optimization (ARO) approach was employed, which is a supervised method to detect credit card fraud. ARO refers to a kind of production in which one parent produces some offspring. By applying this method and sampling just from the majority class, the effectiveness of the classification is increased. A comparison to Artificial Immune Systems (AIS), which is one of the best methods implemented on current datasets, has shown that the proposed method is able to remarkably reduce the required training time and at the same time increase the recall that is important in fraud detection problems. The obtained results show that ARO achieves the best cost in a short time, and consequently, it can be considered a real-time fraud detection system

Strengths, Opportunities and areas of Improvements for Maroof Platform in Saudi Arabia

Maroof is a new third-party platform that is managed by the Saudi Ministry of Commerce. Maroof is designed to evaluate, regulate, and organize stores and E-commerce practices in Saudi Arabia. This paper will examine the platforms\u27 strengths, opportunities, and recommendations for improvements. Maroof was designed to help buyers make purchase decisions and issue certificates to registered stores. A major strength of the platform is that sellers are encouraged to sign up with their social security number, which makes them known\u27\u27 to the Saudi Ministry of Commerce. Additionally, it legitimizes the store owners\u27 credentials. Therefore, Saudi citizens can feel more confident when purchasing goods from social media accounts that are registered with Maroof. Utilizing Maroof is one of the factors that increase trust in buying in Saudi Arabia, especially in E-commerce. The purpose of Maroof is to prevent any fraudulent activities as the platform allows buyers to report a claim easily. On the other hand, the Maroof is a new platform with a major shortcoming, and thus there are several opportunities to improve Maroof\u27s usability. The major area that could use improvement is the comments section. For instance, a registered sign in username and password is not required to post a review. The platform simply allows users to anonymously write product reviews and comments along with ratings of sellers or stores using their social media accounts. This paper\u27s aim is to review these comments on the Maroof platform, which is a supposed, reliable, and trusted governmental website. Although the Maroof team claims they are continuously working on detecting fake reviews, and the Ministry of Commerce states that Maroof provides authenticated reviews, findings of this paper show that there are many fake positive reviews on Maroof. As a result, the Saudi Ministry of Commerce should make it clear that ratings do not always represent the quality of a product, even on a governmental website