The advertising network considered as the middle man in web advertising between advertisers and publishers. This paper presented an intelligent and memory efficient Fraud detection technique with intelligent classification engine to be used by the advertising networks to scan clicks and impressions offline streams happen on publisher side for the purpose of detecting click fraud and impression ...

Reported dollar losses from online auction fraud were over $43M in 2008 in the US (NW3C, 2009). In general, reputation systems provided by online auction sites are the most common countermeasure available for buyers to evaluate a seller’s credit. Unfortunately, feedback score mechanisms are too easily manipulated, creating falsely overrated reputations. In addition, existing research on online ...

Online lending has exploded in China in recent years. However, the €nancial agents are vulnerable for fraud aŠacks which reults in huge €nancial losses. Anti-fraud detection methods for traditional €nancial services are less e‚ective against online frauds. As a group e‚ort at CreditX, we designed an accurate, ecient, and scalable online fraud detecting mechnism by delivering a behavior languag...

Extensive research has been done on the analytical and empirical examination of financial data in annual reports to detect fraud; however, there is scant research on the analysis of text in annual reports to detect fraud. The basic premise of this research is that there are clues hidden in the text that can be detected to determine the likelihood of fraud. In this research, we examine both the ...

© 2007 GCX Advanced Analytics LLC 1 www.gcxanalytics.com Fraud risk managers are interested in detecting and preventing fraud, but when it comes to making a business case to management for a new, analytics-based, detection system, it is frequently difficult to quantify the benefits of the system. Even if all the other parts of the system are fine from a software application perspective (alert m...

This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incomin...

Benford’s Law [1] specifies the probabilistic distribution of digits for many commonly occurring phenomena, ideally when we have complete data of the phenomena. We enhance this digital analysis technique with an unsupervised learning method to handle situations where data is incomplete. We apply this method to the detection of fraud and abuse in health insurance claims using real health insuran...

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...

A common method for text-analysis and text-based classification is to process term-frequency or patterns of terms. However, these features alone may not be able differentiate fake authentic job advertisements. Thus, in this work, we proposed a detect recruitments using novel set designed reflect the behavior fraudsters who present information. The were missing information, exaggeration, credibi...