An Intelligent Data Mining System to Detect Health Care Fraud

The chapter begins with an overview of the types of healthcare fraud. Next, there is a brief discussion of issues with the current fraud detection approaches. The chapter then develops information technology based approaches and illustrates how these technologies can improve current practice. Finally, there is a summary of the major findings and the implications for healthcare practice

A framework for internal fraud risk reduction at it integrating business processes : the IFR² framework

Fraud is a million dollar business and it is increasing every year. Both internal and external fraud present a substantial cost to our economy worldwide. A review of the academic literature learns that the academic community only addresses external fraud and how to detect this type of fraud. Little or no effort to our knowledge has been put in investigating how to prevent ánd to detect internal fraud, which we call ‘internal fraud risk reduction’. Taking together the urge for research in internal fraud and the lack of it in academic literature, research to reduce internal fraud risk is pivotal. Only after having a framework in which to implement empirical research, this topic can further be investigated. In this paper we present the IFR² framework, deduced from both the academic literature and from current business practices, where the core of this framework suggests to use a data mining approach.El fraude es un negocio millonario y está aumentando cada año. Tanto el fraude interno como el externo presentan un coste considerable para nuestra economía en todo el mundo. Este artículo sobre la literatura académica enseña que la comunidad académica solo se dirige al fraude externo, y cómo se detecta este tipo de fraude. Que sepamos, se ha hecho poco o ningún esfuerzo en investigar cómo evitar y detectar el fraude interno, al que llamamos ‘reducción del riesgo de fraude interno’. Teniendo en cuenta la urgencia de investigar el fraude interno, y la ausencia de ello en la literatura académica, la investigación para reducir este tipo de fraude es esencial. Este tema puede ser aún investigado con mayor profundidad solo después de tener un marco, en el que implementar investigación empírica. En este artículo, presentamos el marco IFR, deducido tanto de la literatura académica como de las prácticas empresariales actuales, donde el foco del marco sugiere usar un enfoque de extracción de datos

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

INTERNAL CONTROL AND FRAUD PREVENTION: PRIOR RESEARCH ANALYSIS

The focus of this study is to analyze prior research on fraud detection and prevention. Most researchers agree that strong internal controls are an influencing factor on fair financial reporting and fraud prevention and detection. Financial statement and employee fraud can be very expensive to businesses and the economy as a whole. The establishment and evaluation of the internal control methods and procedures can decrease fraudulent events and losses. Accounting professionals, CPA’s, and tax preparers are the first to detect “red flags” in business activities and must work together with boards of directors, CFO’s, and small business owners. Simple methods, such as ratio analyses can help to signal early signs of fraudulent events and prevent future damages.  Implementation of fraud prevention measures are the most efficient deterrent. Some of the most effective controls like, job rotation, mandatory vacations, training, fraud hotlines, and surprise audits, need not be expensive and should be employed by all businesses. Unfortunately, the most important and effective fraud prevention techniques are seldom applied by businesses. Surprisingly, the least effective and most expensive measures, like external audits, are more frequently employed. As reported in this review of the literature, most businesses focus on fraud detection, while fraud prevention and implementing proper internal controls would result in better prevention of financial losses. DOI: https://doi.org/10.15544/ssaf.2014.1

Case study: an analytical model for the fraud detection In company purchases

Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementIn a world where the business landscape is changing as a consequence of the increasing importance of the digital area, the financial and reporting environment are also being reshaped, resulting in several challenges for audit committees and auditors. Assurance services are responsible for transmitting clear information and nowadays auditing has become an increasingly demanding task. In this regard, detection fraud is one of the areas explored by assurance, including studying the risk of companies committing fraud, and also the hypothesis of employees committing these kinds of misconduct. In fact, in the modern digital world, it becomes easier to commit fraud, therefore it is quite relevant to study its impacts and causes. Theories related to the fraud triangle as well as fraud related to the utilities sector will be explored and will be the basis of this study. Having this in mind, this study aims to identify the most significant variables in detecting the risk of fraud in company purchases, using some companies’ data in order to help this analysis. Having this in mind, the conclusions about the selected model were to consider two different approaches: Keeping All Variables and Removing Some Variables. For the first option, the best model was Linear Regression and for the other one was Neural Networks, considering Misclassification Rate and Captured Response as significant statistics. Thus, this study aims to fill the gap of information and studies in this area by providing relevant inputs that may be used on other studies in this field