10,823 research outputs found

    A Framework for Occupational Fraud Detection by Social Network Analysis

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    International audienceThis paper explores issues related to occupational fraud detection. We observe over the past years, a broad use of network research across social and physical sciences including but not limited to social sharing and filtering, recommendation systems, marketing and customer intelligence, counter intelligence and law enforcement. However, the rate of social network analysis adoption in organizations by control professionals or even by academics for insider fraud detection purpose is still very low. This paper introduces the OFD – Occupational Fraud Detection framework, based on formal social network analysis and semantic reasoning principles by taking a design science research perspective

    Occupational Fraud Detection Through Visualization

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    Occupational fraud affects many companies worldwide causing them economic loss and liability issues towards their customers and other involved entities. Detecting internal fraud in a company requires significant effort and, unfortunately cannot be entirely prevented. The internal auditors have to process a huge amount of data produced by diverse systems, which are in most cases in textual form, with little automated support. In this paper, we exploit the advantages of information visualization and present a system that aims to detect occupational fraud in systems which involve a pair of entities (e.g., an employee and a client) and periodic activity. The main visualization is based on a spiral system on which the events are drawn appropriately according to their time-stamp. Suspicious events are considered those which appear along the same radius or on close radii of the spiral. Before producing the visualization, the system ranks both involved entities according to the specifications of the internal auditor and generates a video file of the activity such that events with strong evidence of fraud appear first in the video. The system is also equipped with several different visualizations and mechanisms in order to meet the requirements of an internal fraud detection system

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

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    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

    A Framework for Internal Fraud Risk Reduction at IT Integrating Business Processes: The IFR² Framework

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    IT-based Fraud Management Approaches in Small and Medium Enterprises – A Multivocal Literature Review

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    Fraud, particularly cybercrime, is an emerging worldwide risk. Despite this, the risk of fraud appears underestimated in discussions of fraud mitigation and risk management in the context of SMEs. This multivocal literature review discusses ways of minimizing fraud for SMEs and IT-supported concepts that are currently proposed in literature. The present review shows that existing concepts often focus on specific or internal fraud risks and organizational countermeasures, but rarely cover newer fraud risks or suggest IT-supported measures to reduce the risk of fraud for SMEs. However, some IT security approaches have been proposed to mitigate fraud, but the area of internal control concepts of compliance and governance appears unconnected to IS approaches. This review identifies a lack of integrated fraud-management concepts, which is surprising due to the omnipresence of ICT, it found limitations in existing concepts and suggests areas for future IS research and academic discussion
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