This research is a descriptive analysis answering the question, what measures are currently taken by the leadership―boards of trustees and superintendents of schools―of Texas school districts to prevent embezzlement? The research perspective utilized was quantitative with a descriptive, cross-sectional design. Data collection was accomplished through a survey with questions constructed from the most commonly recommended strategies discovered through the review of literature. The survey was distributed to the 1031 superintendents of school districts in Texas via email. The response rate was 33% or 339 returned surveys. The data set created concentrates on the four most common preventive measures: policy and procedure, management, auditing, and ethics. These measures are considered as they function to interrupt the principles of the fraud triangle. Comparisons were completed regarding region, district size, superintendent tenure and superintendent experience. Policy adoption was found to be extremely widespread. Procedures written to fully implement policy were less prevalent. Review of management practices found problems concerning credit cards, personnel evaluations, and password access to multiple computer finance recordkeeping systems concentrated in one employee. External auditing programs were universal due to statutory mandate but internal auditors and internal audit committees were few. Ethics training for business office personnel existed but with little consistent application across districts. The adoption of a code of ethics for business office personnel was rare. Recommendations made were that school leaders should be educated concerning appropriate actions in the common prevention areas. They need an to understand the importance of internal auditing, know the language in local policy, and they need to write procedures.

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

This study uses the principal-agent framework to investigate the trade-off between the benefits of internal control stemming from a reduction of the losses from inappropriate employee actions and the cost of implementing it brought about by the possibility of collusion that it creates. It is shown that, when the agents find it relatively easy to collude, implementing internal control reduces agency welfare, defined as the sum of expected payments accruing to the principal and the agents, even as, with positive transaction costs of collusion, it improves productive efficiency, defined as the expected output. As a result, the principal, under certain conditions, finds it in her best interest to use internal control as a threat instead of implementing it. When this is the case, the principal sometimes prefers to decrease the accuracy of the accounting information system. The analysis of the agents' side contracting indicates that, even if the principal can prevent explicit collusion, for some values of parameters the possibility of tacit collusion still results in a loss. The study also investigates the effect of the choice of organizational form on the value of internal control. The analysis of two different versions of the model demonstrates that, for a wide range of parameters, creating a hierarchical structure reduces, albeit does not eliminate, the loss from collusion -- i.e., internal control and hierarchical delegation are complementary instruments of organizational design. It is also shown that, when one agent is ex ante more likely to be efficient than the other, in most cases the principal optimally appoints to the supervisory position the one who is less likely to be efficient. As a result, the supervisor, in expectation, exerts a lower effort level than the subordinate and collects higher salary. / text

Prior research on combating commercial crime has focused predominantly on the responsibilities of auditors and ex post facto forensic investigations. This dissertation aims rather to delve into the meta-theoretical philosophy of commercial crime prevention and the role that forensic accountants can play in this regard, postulating that proactive prevention of commercial crimes is a more effective approach. The BRICS countries (Brazil, Russia, India, China and South Africa) were chosen for deeper level analysis, based on their strong growth potential coupled with high levels of commercial crime. While the majority of the research centred around commercial crime prevention strategies for the BRICS countries, a secondary objective was to expand the research field associated with forensic accounting, so as to encourage research into incorporating more preventative strategies. Subsequently, from the literature review and philosophical analysis performed, this dissertation establishes that developing prevention strategies for commercial crime is a philosophical and also a feasible possibility in the BRICS countries. / MCom (Forensic Accountancy), North-West University, Potchefstroom Campus, 2014

Prior research on combating commercial crime has focused predominantly on the responsibilities of auditors and ex post facto forensic investigations. This dissertation aims rather to delve into the meta-theoretical philosophy of commercial crime prevention and the role that forensic accountants can play in this regard, postulating that proactive prevention of commercial crimes is a more effective approach. The BRICS countries (Brazil, Russia, India, China and South Africa) were chosen for deeper level analysis, based on their strong growth potential coupled with high levels of commercial crime. While the majority of the research centred around commercial crime prevention strategies for the BRICS countries, a secondary objective was to expand the research field associated with forensic accounting, so as to encourage research into incorporating more preventative strategies. Subsequently, from the literature review and philosophical analysis performed, this dissertation establishes that developing prevention strategies for commercial crime is a philosophical and also a feasible possibility in the BRICS countries. / MCom (Forensic Accountancy), North-West University, Potchefstroom Campus, 2014

Frauds conducted online are crimes that are and has been increasing in numbers over the last years. Government reports shows that this is the case in Sweden as well as internationally. As of today the Swedish legal systems lacks a definition and categorization approach for online frauds. This thesis aims at developing such definition and a classification scheme that can be used to classify online frauds. Further, this thesis suggests and evaluates a defense mechanism for use in arenas were online frauds are executed. The results bring a definition and classification scheme that has been developed in cooperation with the Swedish police and validated with a judge from a Swedish court. The evaluation of the suggested defense mechanism indicates that our suggested defense mechanism has the potential to make internet users less susceptible to online fraud attacks.

A remarkable gap exists between the financial impact of fraud in the B2C e-commerce mail order business and the amount of research conducted in this area — whether it be qualitative or quantitative research about fraud prevention. Projecting published fraud rates of only approx. one percent to e-commerce sales data, the affected sales volume amounts to $651 million in the German market, and in the North American market, the volume amounts to $5.22 billion; empirical data, however, indicate even higher fraud rates. Low profit margins amplify the financial damage caused by fraudulent activities. Hence, companies show increasing concern for raising numbers of internet fraud. The problem motivates companies to invest into data analytics and, as a more sophisticated approach, into automated machine learning systems in order to inspect and evaluate the high volume of transactions in which potential fraud cases can be buried. In other areas that face fraud (e.g. automobile insurance), machine learning has been applied successfully. However, there is little evidence yet about which variables may act as fraud risk indicators and how to design such systems in the e-commerce mail order business. In this research, mixed methods are applied in order to investigate the question how computer-aided systems can help detect and prevent fraudulent transactions. In the qualitative part, experts from fraud prevention companies are interviewed in order to understand how fraud prevention has been conventionally conducted in the e-commerce mail order business. The quantitative part, for which a dataset containing transactions from one of the largest e-commerce firms in Europe has been analyzed, consists of three analytical components: First, feature importance is evaluated by computing information gain and training a decision tree in order to find out which features are relevant fraud indicators. Second, a prediction model is built using logistic regression and gradient boosted trees. The prediction model allows to estimate the fraud risk of future transactions. Third, because risk estimation alone does not equal profit maximization, utility theory is woven into prioritization of transactions such that the model optimizes the financial value of fraud prevention activities. Results indicate that the interviewed companies want to use intelligent computer-aided systems that support manual inspection activities through the use of data mining techniques. Feature analysis reveals that some features, such as whether a shipment has been sent to a parcel shop, can help separate fraudulent from legitimate orders better than others. The predictive model yields promising results as it is able to correctly identify approximately 86% of the 2% most suspicious transactions as fraud. When the model is used to optimize the financial outcome instead of pure classification quality, results suggest that the company providing the dataset could achieve substantial additional savings of up to 87% through introduction of expected utility as a ranking measure when being constrained by limited inspection resources.

El presente trabajo de investigación tiene como objetivo demostrar la importancia que tiene la gestión de riesgos, principalmente basado en COSO ERM 2017 y su influencia en la prevención de fraude en las empresas del sector industrial que cotizan en la Bolsa de Valores de Lima. El trabajo consta de un marco teórico en el cuál se define dos temas importantes: la gestión de riesgos – COSO ERM 2017 y, la prevención de fraude. En segundo lugar, se encuentra el plan de investigación estableciendo el problema, hipótesis y objetivos de la investigación, así como la metodología a utilizarse. Para el desarrollo del presente trabajo, hemos realizado una investigación cualitativa. Donde, se empleó el desarrollo de las entrevistas a profundidad a especialistas en el tema de gestión de riesgos y encuestas personales de las principales empresas del sector industrial que cotizan en la Bolsa de Valores de Lima con la finalidad de determinar si realizar una gestión de riesgos basada en el modelo COSO ERM 2017 ayuda en la prevención de fraude. Asimismo, desarrollamos un caso práctico donde se evaluó la situación actual respecto al uso de una adecuada gestión de riesgos basada en el modelo COSO ERM 2017 y su influencia en la prevención de fraude de la empresa líder del sector industrial de cerámicos que cotiza en la Bolsa de Valores de Lima. Los resultados de la investigación demuestran que las empresas que se desempeñan en el sector industrial no cuentan con un conocimiento sobre cómo se tiene que realizar una adecuada gestión de riesgos basada en el modelo COSO ERM 2017, debido a que solamente lo relacionan con la eficiencia en el manejo de los gastos y que la persona responsable es el contador. En el caso de la prevención de fraude, las organizaciones tenían un mayor conocimiento, pero al momento de consultarles por su planeamiento estratégico, afirmaban que la información era informada de manera oral. Ante esto, podemos concluir que el COSO ERM 2017 tiene un soporte y una influencia significativa en el proceso de prevención de fraude de una organización, debido a que proporciona una mayor comprensión de la gestión del riesgo cuando la organización establece y ejecuta sus estrategias. También una correcta implementación del COSO ERM 2017 permite que una empresa tenga mayor seguridad, objetivos más claros y un mayor énfasis en la evaluación de riesgos. / The objective of this research project is to demonstrate the importance of risk management, mainly based on COSO ERM 2017 and how it influences on fraud prevention in industrial sector companies that are listed on the Lima Stock Exchange. The project consists of a theoretical framework, that includes two main problems: risk management – COSO ERM 2017 and fraud prevention. Then, there is the research plan that establish the problem, hypothesis and the objectives of the research, as well the methodology to be used. For this project development, we conducted a qualitative research. It was used deep interviews with specialists in the risk management area and surveys of the main companies in the industrial sector that are listed on the Lima Stock Exchange with the objective of determining how much knowledge they have about and how frequently they use risk management based on COSO ERM 2017 model and fraud prevention. Likewise, we developed a case study where we evaluated the current situation of regarding the use of a proper risk management based on COSO ERM 2017 model and its influence in the fraud prevention of the leading company in the ceramic industry that is listed on the Lima Stock Exchange. The results of the research show that companies that work in the industrial sector do not have enought knowledge about the importance of an adequate risk management based on COSO ERM 2017 model, due to they only relate it to efficiency in expenses management which corresponds to an accountant. In the case of fraud prevention, the organizations had greater knowledge, but at the time of consulting them about their strategic planning, they affirmed that the information was only orally informed. Given this, we can conclude that the COSO ERM 2017 has a support and an important influence in the fraud prevention process of an organization, because it provides a greater understanding of risk management when the organization establishes and excutes its strategies. Also a correct implementation of COSO ERM 2017 allows a company to have greater security, clearer objectives and a greater emphasis on risk assessment. / Tesis

The economic cost of financial statement fraud continues to be a problem for organizations and society. The research problem addressed in this study was the limited risk management strategies available for the early detection and prevention of financial statement fraud by corporate managers and auditors. These strategies are important to the proactive prevention of fraud. This study is important to future trustworthiness of financial statements. The purpose of this qualitative, multiple-case study was to explore current early detection and prevention methods in financial statement fraud using a risk management conceptual framework. The research question focused on current fraud detection and prevention policies and risk management strategies that are currently used for proactively detecting and preventing financial statement fraud. Multiple sources of information were used, including examining recent financial fraud scandals, interviews, documents, and past research. The target population was managers and auditors of publicly traded corporations. A purposive sampling procedure was used to select 23 participants, which provided rich data. The qualitative data was coded and analyzed using the concept of risk management, along with triangulation to ensure credibility. The key findings indicated that current practitioners are moving beyond the era of reactive measures born from the past fraud crises and are working toward improved financial statement quality and trust. The results of the study also indicated that future research should include proactive methods of preventing fraud. This study is socially significant because it could enhance the ability to trust financial statement reporting in the future and improve corporate reputations.

M.Sc. (Computer Science) / The past couple of years have seen an explosion in the number of online fraud schemes – Total annual losses exceed tens of millions of Rands. Many people and organizations from all over the world have fallen victim to it. Nobody is safe; everybody is vulnerable. As we increasingly make use of the Internet and mobile technology to do our work and to perform chores such as online banking or shopping, we become even more vulnerable. Fraudsters make use of ever-more sophisticated techniques and clever schemes to target the unsuspecting end-users of mobile and Internet technology, and to trick them into surrendering their personal information so that electronic transactions can be carried out in their name. Examples include cheque and credit card fraud, phishing, identity theft and spyware, to name but a few. Services such as Internet- and cell phone banking especially, provide a haven of possibilities to make easy money because the technology is relatively new, and it is being used by evermore people who believe that it is fast, safe and secure and will therefore make their lives easier. One of the latest scams at the time of this writing is “SIM swap fraud”: Fraudsters target specific victims, perform SIM swaps on their cell phone numbers, and then proceed to empty the victims’ bank accounts. This is all done in a matter of minutes, so the victims only realize what has happened when it is too late to do anything about it. Needless to say, a solution must be found that will prevent unauthorized SIM swaps and strengthen online banking security. This dissertation does exactly that. It examines the digital world known as cyberspace, identifies how SIM swap fraudsters manage to defraud their targets, and presents a biometrics-based security system to combat SIM swap fraud.