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Author Caldeira, E. ♦ Brandao, G. ♦ Pereira, A.C.M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2014
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword e-Commerce ♦ Fraud Prevention ♦ Neural networks ♦ e-Payment ♦ e-Business ♦ Credit cards ♦ Bayes methods ♦ Mathematical model ♦ Data mining ♦ Machine Learning ♦ Logistics
Abstract The volume of electronic transactions has raised significantly in last years, mainly due to the popularization of electronic commerce (e-commerce), such as online retailers (e.g., Amazon.com, eBay, Ali Express.com). We also observe a significant increase in the number of fraud cases, resulting in billions of dollars losses each year worldwide. Therefore it is important and necessary to developed and apply techniques that can assist in fraud detection and prevention, which motivates our research. This work aims to apply and evaluate computational intelligence techniques (e.g., Data mining and machine learning) to identify fraud in electronic transactions, more specifically in credit card operations performed by Web payment gateways. In order to evaluate the techniques, we apply and evaluate them in an actual dataset of the most popular Brazilian electronic payment service. Our results show good performance in fraud detection, presenting gains up to 43 percent of an economic metric, when compared to the actual scenario of the company.
Description Author affiliation: Comput. Dept., Fed. Center of Technol. Educ. of Minas Gerais (CEFET-MG), Belo Horizonte, Brazil (Caldeira, E.; Brandao, G.) || Dept. of Comput. Sci., Fed. Univ. of Minas Gerais (UFMG), Belo Horizonte, Brazil (Pereira, A.C.M.)
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-10-22
Publisher Place Brazil
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781479969531
Size (in Bytes) 411.50 kB
Page Count 8
Starting Page 42
Ending Page 49


Source: IEEE Xplore Digital Library