Every year, e-service providers report losses of billions of dollars due to fraud. Despite their huge efforts in implementing sophisticated fraud detection systems on top of their e-services, fraud effects seem to be rather increasing than decreasing. As a result, fraud risk assessment has been introduced as a fundamental part of e-service providers’ prevention strategies. In particular, identi...

Telecom providers are losing tremendous amounts of money due to fraud risks posed to Telecom services and products. Currently, they are mainly focusing on fraud detection approaches to reduce the impact of fraud risks against their services. However, fraud prevention approaches should also be investigated in order to further reduce fraud risks and improve the revenue of Telecom providers. Fraud...

A new approach to detect fraudulent event patterns in the field of insurance fraud detection by using a combination of discriminant analysis and neural network techniques is presented. The approach is embedded in a Complex Event Processing (CEP) engine. CEP is an emerging technology for detecting known patterns of events and aggregating them as complex events at a higher level of analysis in re...

This paper describes an effective medical claim fraud/abuse detection system based on data mining used by a Chilean private health insurance company. Fraud and abuse in medical claims have become a major concern within health insurance companies in Chile the last years due to the increasing losses in revenues. Processing medical claims is an exhausting manual task carried out by a few medical e...

This 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 organizati...

Every year billions of Euros are lost worldwide due to credit card fraud. Thus, forcing financial institutions to continuously improve their fraud detection systems. In recent years, several studies have proposed the use of machine learning and data mining techniques to address this problem. However, most studies used some sort of misclassification measure to evaluate the different solutions, a...

Since the evolution of the internet, many small and large companies have moved their businesses to the internet to provide services to customers worldwide. Cyber credit‐card fraud or no card present fraud is increasingly rampant in the recent years for the reason that the credit‐card i s majorly used to request payments by these companies on the internet. Therefore the need to ensure secured tr...

We present a social simulation model that covers three main financial services: Banks, Retail Stores, and Payments systems. Our aim is to address the problem of a lack of public data sets for fraud detection research in each of these domains, and provide a variety of fraud scenarios such as money laundering, sales fraud (based on refunds and discounts), and credit card fraud. Currently, there i...