Nowadays the customers prefer the most accepted payment mode via credit card for the convenient way of online shopping, paying bills in easiest way. At the same time the fraud transaction risks using credit card is a main problem which should be avoided. There are many data mining techniques available to avoid these risks effectively. In existing research they modelled the sequence of operation...

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 ...

Why are auditors unable to detect fraudulent financial reporting in some audits? Should auditors be able to anticipate when fraud is likely to occur? Various studies have discussed not only the need for experience and supervision of auditors, but also the effect of decision models, and even expert systems, on fraud detection and the study of internal controls. This paper presents a discussion o...

All over the world we have been assisting to a significant increase of the telecommunication systems usage. People are faced day after day with strong marketing campaigns seeking their attention to new telecommunication products and services. Telecommunication companies struggle in a high competitive business arena. It seems that their efforts were well done, because customers are strongly adop...

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...

We present a new approach to cross channel fraud detection: build graphs representing transactions from all channels and use analytics on features extracted from these graphs. Our underlying hypothesis is community based fraud detection: an account (holder) performs normal or trusted transactions within a community that is “local” to the account. We explore several notions of community based on...

Outlier detection is useful for credit card fraud detection. Due to drastic increase in digital frauds, there is a lot of financial losses and therefore various techniques are developed for fraud detection and applied to diverse business fields. In high-dimensional data, outlier detection presents some challenges because of increment of dimensionality. In this paper, the proposed model aims to ...

Purpose – The purpose of this study is to examine the extent to which accountants, internal auditors, and certified fraud examiners use fraud prevention and detection methods, and their perceptions regarding the effectiveness of these methods. Design/methodology/approach – A survey was administered to 86 accountants, internal auditors and certified fraud examiners. Findings – The results indica...

In the year 2009 several data privacy scandals have hit the headlines where major corporations had a legitimate need for detecting fraud conducted by their own employees, but chose inappropriate measures for data screening. This contribution presents architectures and pseudonymization technology for privacy compliant fraud screening or fraud detection, in order to reduce the number of undiscove...

Spam issues have become worse on social media platforms and apps with the growth of IoT. To solve problem, researchers suggested several spam detection techniques. rates are still high despite use anti-spam technologies tactics, especially given ubiquity rogue e-mails that lead to dangerous websites. By using up memory or storage space, may cause servers run slowly. One most essential methods f...