Using 629 observations of U.S. publicly listed firms with internal control related frauds from 2000 to 2006; this study investigates the change in auditor litigations in the Post- Sarbanes Oxley, Section 404 period. To the extent the conditions of the internal control in place are inadequate or non-existent, the possibility of the occurrence of internal control related fraud heightens. Thus, the inability of auditors to detect a financial statement misstatement due to internal control fraud in a timely manner exposes auditors to litigation (Barra, 2010; Heninger, 2001; Caplan, 1999). This situation was prevalent in the recent notable corporate failures that resulted in auditors being named as potential defendants. The present research finding indicates during the Post-SOX 404 period, the probability of auditor litigation due to internal control fraud increases. However, no support was shown for further increases in the likelihood of auditor litigation when both types of fraud occur in the Post-SOX 404 period. These results suggest an increase in the enforcement of accountability by the SEC, and should motivate auditors towards reassessing their audit procedures. Furthermore, the results indicate the probability of auditor litigation due to internal control fraud decreases for accelerated filers, and similarly, the probability of auditor litigation decreases for firms with management voluntary disclosures reflecting effective internal control. The overall result of this study indicates the likelihood of auditors being litigated increased in the Post-SOX 404 period, and auditors are more likely to be litigated when both types of fraud occurs simultaneously. This result further supports the argument for meritorious claims and the procedural justice theory.

I The crime of fraud and special kinds of fraud ABSTRACT When choosing a subject matter for my diploma thesis I focused on what might be useful even from the point of view of my future practice. In this context, fraud of all different kinds is something we can meet with on daily basis and that is the reason why I decided to study in detail and treat this particular phenomenon. The entire thesis has been divided by me into six chapters with each of them splitting further into sub-chapters. I wished to treat the subject matter in most comprehensive way and so the thesis contains both historical and descriptive aspects as well as methodological ones, with an emphasis on the use and interpretation applied by courts and specific institutions. Chapter One stands for an introduction into the subject matter seen from a historical perspective. The first sub-chapter summarizes re-codification works of penal law from 1989 up to the present time while the subsequent sub-chapters deal with the very term of criminal offence of fraud in respect of its evolution and major amendments. The essence of Chapter Two consists of an analysis of legal attributes of the criminal offence of fraud pursuant to Art. 209, Penal Code (Art. 250, former Penal Code). The individual sub-chapters present general characteristics, definition of...

Nowadays effective Criminal code, No. 40/2009 Coll., contains the criminal offence of a fraud (Section 209) and it's special cases such as the insurance (Section 210), loan (Section 211) and subsidy fraud (Section 212). Nevertheless, the situation hasn't been always like this. Less than twenty years ago the Czech effective legislature contained only the criminal offence of the so called "general" fraud. However the impossibility to persecute all of the fraudulent delinquency by applying the "general" fraud section led the legislator to amend the Criminal Code by adding three above mentioned special sections. The imperfection of the legal system in regards to the fraudulent behaviour (especially related to banks and insurance companies) in the 1990's had dramatically effected the economy of the country and formed a negative prejudice and inauspicious experience with privatisation of the state property etc. among the entire society. These days during the global financial recession has the number of fraudulent behaviour risen significantly, since the lack of procurements, the low employment rate, the general indebtedness etc. bring the debtors to the very boarder of the financial cliff of insolvency and "force" them to commit criminal offences. Therefore, it's highly important to use special tools to...

In 1832, fishermen pulled a full-body bronze sculpture of a youth, now called the Piombino Apollo, from the sea near ancient Populonia. Under life-size, the piece resembles an Archaic kouros, though it has some notable unusual features including an inscription dedicating the supposed image of Apollo to Athena and the signatures of two artists found on a lead tablet hidden within the hollow bronze. These unusual features led scholars to eventually reclassify the piece from an Archaic work of the fifth century to an Archaistic forgery of the second or first century. Few have challenged this reclassification, but this thesis attempts to complicate the application of the word forgery to the Piombino Apollo. Further, it examines whether a contemporary buyer would have been fooled by the sculpture’s “deceptive” traits and offers alternative possibilities to account for the artists’ choices of style, pose, and inscriptions.

Este trabalho identifica sob o contexto da tecnologia, negócio, engenharia social e investigação a ocorrência de fraudes sobre o ambiente Internet Banking. A pesquisa relata a evolução dos métodos utilizados pelos fraudadores para efetivação da fraude desde seu o início, no ano de 2002 à evolução na sofisticação dos meios utilizados para os ataques até meados de 2005. Como a análise se baseou em um estudo de caso, coletou-se um número quantitativo de incidentes no período de um ano permitindo entender neste escopo a tendência de ataques aos clientes de serviços Internet Banking. E com pleno domínio do assunto, o trabalho traz recomendações para a contenção destes incidentes, através de três linhas de ação; sobre usuários finais, provedores e sobre o fraudador. / This research identifies under the technology, business, social engineering and inquiry context the occurrence of fraud on Internet Banking environment. It covers the evolution of the methods used for deceivers since from the beginning, in the year of 2002, and his evolution in the sophistication in several ways used for attacks until 2005. The analysis is based on a case study and a quantitative number of incidents in the period of one year were collected making possible to see the point of such purpose the trend of attacks on Interne t Banking customers. With full domain of this one’s subject, this research brings suggest for incident containment three lines of action; on final users, suppliers and deceivers.

Healthcare is an integral component in peoples lives, especially for the rising elderly population, and must be affordable. The United States Medicare program is vital in serving the needs of the elderly. The growing number of people enrolled in the Medicare program, along with the enormous volume of money involved, increases the appeal for, and risk of, fraudulent activities. For many real-world applications, including Medicare fraud, the interesting observations tend to be less frequent than the normative observations. This difference between the normal observations and those observations of interest can create highly imbalanced datasets. The problem of class imbalance, to include the classification of rare cases indicating extreme class imbalance, is an important and well-studied area in machine learning. The effects of class imbalance with big data in the real-world Medicare fraud application domain, however, is limited. In particular, the impact of detecting fraud in Medicare claims is critical in lessening the financial and personal impacts of these transgressions. Fortunately, the healthcare domain is one such area where the successful detection of fraud can garner meaningful positive results. The application of machine learning techniques, plus methods to mitigate the adverse effects of class imbalance and rarity, can be used to detect fraud and lessen the impacts for all Medicare beneficiaries. This dissertation presents the application of machine learning approaches to detect Medicare provider claims fraud in the United States. We discuss novel techniques to process three big Medicare datasets and create a new, combined dataset, which includes mapping fraud labels associated with known excluded providers. We investigate the ability of machine learning techniques, unsupervised and supervised, to detect Medicare claims fraud and leverage data sampling methods to lessen the impact of class imbalance and increase fraud detection performance. Additionally, we extend the study of class imbalance to assess the impacts of rare cases in big data for Medicare fraud detection. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection

Este trabalho identifica sob o contexto da tecnologia, negócio, engenharia social e investigação a ocorrência de fraudes sobre o ambiente Internet Banking. A pesquisa relata a evolução dos métodos utilizados pelos fraudadores para efetivação da fraude desde seu o início, no ano de 2002 à evolução na sofisticação dos meios utilizados para os ataques até meados de 2005. Como a análise se baseou em um estudo de caso, coletou-se um número quantitativo de incidentes no período de um ano permitindo entender neste escopo a tendência de ataques aos clientes de serviços Internet Banking. E com pleno domínio do assunto, o trabalho traz recomendações para a contenção destes incidentes, através de três linhas de ação; sobre usuários finais, provedores e sobre o fraudador. / This research identifies under the technology, business, social engineering and inquiry context the occurrence of fraud on Internet Banking environment. It covers the evolution of the methods used for deceivers since from the beginning, in the year of 2002, and his evolution in the sophistication in several ways used for attacks until 2005. The analysis is based on a case study and a quantitative number of incidents in the period of one year were collected making possible to see the point of such purpose the trend of attacks on Interne t Banking customers. With full domain of this one’s subject, this research brings suggest for incident containment three lines of action; on final users, suppliers and deceivers.

Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in many real-world applications, e.g. anomaly detection. Modeling such skewed data distributions is often very difficult, and non-standard methods are sometimes required to combat these negative effects. These challenges have been studied thoroughly using traditional machine learning algorithms, but very little empirical work exists in the area of deep learning with class imbalanced big data. Following an in-depth survey of deep learning methods for addressing class imbalance, we evaluate various methods for addressing imbalance on the task of detecting Medicare fraud, a big data problem characterized by extreme class imbalance. Case studies herein demonstrate the impact of class imbalance on neural networks, evaluate the efficacy of data-level and algorithm-level methods, and achieve state-of-the-art results on the given Medicare data set. Results indicate that combining under-sampling and over-sampling maximizes both performance and efficiency. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 132-152).

This thesis explores if fraud or mismanagement in municipal governments can be diagnosed or detected in advance of their bankruptcies by financial statement analysis using Benford’s Law. Benford’s Law essentially states that the distribution of first digits from real world observations would not be uniform, but instead follow a trend where numbers with lower first digits (1, 2…) occur more frequently than those with higher first digits (…8,9). If a data set does not follow Benford’s distribution, it is likely that the data has been manipulated. This widespread phenomenon has been used as a tool to detect anomalies in data sets. The annual financial statements of Jefferson County, Vallejo City, and Orange County were analyzed. All the data sets showed overall nonconformity to Benford’s Law and therefore indicated that there was the possibility of fraud occurring. I find that Benford’s Law, had it been applied in real time to those financial statements, would have been able to detect that something was amiss. That would have been very useful because each of those jurisdictions subsequently went bankrupt. This paper demonstrates that Benford’s Law may in some cases be useful as an early indicator to detect the possibility of fraud in municipal governments’ financial data.