In the context of 4.0 technology revolution, which develops and applies strongly in many fields, banking sector is considered to be leading one, application algorithms detect fraud extremely important. necessary. recent years, credit card transactions including physical payments online have become increasingly popular countries around world. This convenient payment method attracts more criminal...

Currently peer review is thought to be slow, expensive, profligate of academic time, highly subjective, prone to bias, easily abused, poor at detecting gross defects, and almost useless for detecting fraud. One cannot predict the future but at present there do not seem to be serious alternatives to peer review. Peer review has been structurally static since the nineteenth century mainly through...

erious allegations of fraud have been made with respect to Russia’s first competitive, party-based parliamentary election in December 1993. Although similar allegations have been made with respect to the 1995 parliamentary and 1996 presidential elections, those that concern 1993 are especially problematic. The assertion that over nine million ballots were fraudulently cast and that the turnout ...

As there is a vast advancement in the E-commerce technology, the use of credit cards has grown up. The credit card has become the crucial mode of payment so with the rise in the credit card transactions, the credit card frauds have also become frequent nowadays. [1] Thus, an improved fraud detection system has become essential to maintain the reliability of the payment system. The criterion is ...

Prescription fraud is a main problem that causes substantial monetary loss in health care systems. We aimed to develop a model for detecting cases of prescription fraud and test it on real world data from a large multi-center medical prescription database. Conventionally, prescription fraud detection is conducted on random samples by human experts. However, the samples might be misleading and m...

Detecting suspicious or malicious user behavior in large networks is an essential task for administrators which requires significant effort due to the huge amount of log data to be processed. However, several of these activities can be rapidly identified since they usually demonstrate periodic behavior. For instance, periodic activities by specific users accessing the billing system of a financ...

Data mining is becoming strategically important area for many business organizations including banking sector. It is a process of analyzing the data from various perspectives and summarizing it into valuable information. Data mining assists the banks to look for hidden pattern in a group and discover unknown relationship in the data. Today, customers have so many opinions with regard to where t...

Fraud detection has been an important topic of research in the data mining community for the past two decades. Supervised, semi-supervised, and unsupervised approaches to fraud detection have been proposed for the telecommunications, credit, insurance and health-care industries. We describe a novel hybrid system for detecting fraud in the highly growing lotteries and online games of chance sect...

This research proposes and implements a heuristic model to detect client-side e-banking fraud caused by malware. Results show that the model is promising and is able to detect malicious injections from malware. To validate the developed model, an additional experiment is performed in which unknown web pages, adapted by recent malware are correctly classified based on historical, malicious pages...

I develop a novel method to detect election fraud from irregular patterns in the distribution of vote-shares. I build on awidely discussed observation that in some electionswhere fraud allegations abound, suspiciously manypolling stations return coarse vote-shares (e.g., 0.50, 0.60, 0.75) for the rulingparty,which seemshighly implausible in large electorates. Using analytical results and simula...