Network visualization for financial crime detection |
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| Affiliation: | 1. Beef & Lamb New Zealand, PO Box 121, Wellington 6140, New Zealand;2. Centre for Computing & Engineering Software Systems, Swinburne University of Technology, PO Box 218, Melbourne, VIC, Australia;3. College of Engineering and Computer Science, Australian National University, Canberra, ACT, Australia;1. University of Oviedo, Computer Science Department, C/Calvo Sotelo s/n, 33007 Oviedo, Spain;2. Alisys Software S.L.U., C/Menendez Valdes 40, 33201 Gijon, Spain;3. University of Oxford, Wolfson College, Linton Road, OX26UD Oxford, UK;1. Department of Environmental Sciences, Louisiana State University, United States;2. Department of Geography, Ghent University, Belgium;3. Department of Educational Studies, Ghent University, Belgium |
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| Abstract: | Objective: We present a new software system, VisFAN, for the visual analysis of financial activity networks.MethodsWe combine enhanced graph drawing techniques to devise novel algorithms and interaction functionalities for the visual exploration of networked data sets, together with tools for SNA and for the automatic generation of reports.ResultsAn application example constructed on real data is presented. We also report the results of a study aimed at qualitatively understanding the satisfaction level of the analysts when using VisFAN.ConclusionVisFAN makes a strong use of visual interactive tools, combined with ad-hoc clustering techniques and customizable layout constraints management.ImplicationsAs this system confirms, information visualization can play a crucial role to face the discovery of financial crimes. |
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| Keywords: | Financial crime detection Graph visualization Social network analysis Information visualization |
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