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Real-Time Fraud Detection: How Stream Computing Can Help the Retail Banking Industry

In: Computers and Technology

Submitted By filipemga
Words 56858
Pages 228
Para os meus pais, porque "o valor das coisas não está no tempo que elas duram, mas na intensidade com que acontecem. Por isso existem momentos inesquecíveis, coisas inexplicáveis e pessoas incomparáveis" como vocês! Obrigado por tudo, Filipe

Abstract
The Retail Banking Industry has been severely affected by fraud over the past few years. Indeed, despite all the research and systems available, fraudsters have been able to outsmart and deceive the banks and their customers. With this in mind, we intend to introduce a novel and multi-purpose technology known as Stream Computing, as the basis for a Fraud Detection solution. Indeed, we believe that this architecture will stimulate research, and more importantly organizations, to invest in Analytics and Statistical Fraud-Scoring to be used in conjunction with the already in-place preventive techniques. Therefore, in this research we explore different strategies to build a Streambased Fraud Detection solution, using advanced Data Mining Algorithms and Statistical Analysis, and show how they lead to increased accuracy in the detection of fraud by at least 78% in our reference dataset. We also discuss how a combination of these strategies can be embedded in a Stream-based application to detect fraud in real-time. From this perspective, our experiments lead to an average processing time of 111,702ms per transaction, while strategies to further improve the performance are discussed. Keywords: Fraud Detection, Stream Computing, Real-Time Analysis, Fraud, Data Mining, Retail Banking Industry, Data Preprocessing, Data Classification, Behavior-based Models, Supervised Analysis, Semi-supervised Analysis

Sammanfattning
Privatbankerna har drabbats hårt av bedrägerier de senaste åren. Bedragare har lyckats kringgå forskning och tillgängliga system och lura bankerna och deras kunder. Därför vill vi införa en ny, polyvalent...

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