Visual Analytics for Fraud Detection: Focusing on Profile Analysis

Abstract
Financial institutions are always interested in ensuring security and quality for their customers. Banks, for instance, need to identify and avoid harmful transactions. In order to detect fraudulent operations, data mining techniques based on customer profile generation and verification are commonly used. However, these approaches are not supported by Visual Analytics techniques yet. We propose a Visual Analytics approach for supporting and fine-tuning profile analysis and reducing false positive alarms.
Description

        
@inproceedings{
10.2312:eurp.20161138
, booktitle = {
EuroVis 2016 - Posters
}, editor = {
Tobias Isenberg and Filip Sadlo
}, title = {{
Visual Analytics for Fraud Detection: Focusing on Profile Analysis
}}, author = {
Leite, Roger Almeida
and
Gschwandtner, Theresia
and
Miksch, Silvia
and
Gstrein, Erich
and
Kuntner, Johannes
}, year = {
2016
}, publisher = {
The Eurographics Association
}, ISSN = {
-
}, ISBN = {
978-3-03868-015-4
}, DOI = {
10.2312/eurp.20161138
} }
Citation