Network Analysis for Financial Fraud Detection

TitleNetwork Analysis for Financial Fraud Detection
Publication TypeConference Paper
Year of Publication2018
AuthorsLeite, R. A., T. Gschwandtner, S. Miksch, E. Gstrein, and J. Kuntner
EditorsPuig, A., and R. Raidou
Conference NameEuroVis 2018 - Posters
PublisherThe Eurographics Association
Conference LocationBrno, Czech Republic
KeywordsBusiness and Finance Visualization, Categories and Subject Descriptors (according to ACM CCS): Human-Centered Computing, Financial Fraud Analysis, Financial Fraud Detection, information visualization, Time Series Data, Visual analytics

Security and quality are main concerns for private and public financial institutions. Data mining techniques based on the profiles of customers of a financial institution are commonly used to avoid fraud and financial damage. However, these approaches often are limited to the analysis of individual customers which hinders the detection of fraudulent networks. We propose a Visual Analytics approach for supporting and fine-tuning customers' network analysis, thus, reducing false-negative alarms of frauds.

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