@conference{472,
  keywords = {Time Series Data, information visualization, Visual analytics, Categories and Subject Descriptors (according to ACM CCS): Human-Centered Computing, Business and Finance Visualization, Financial Fraud Detection, Financial Fraud Analysis},
  author = {Roger Leite and Theresia Gschwandtner and Silvia Miksch and Erich Gstrein and Johannes Kuntner},
  title = {Network Analysis for Financial Fraud Detection},
  abstract = {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.
},
  year = {2018},
  journal = {EuroVis 2018 - Posters},
  publisher = {The Eurographics Association},
  address = {Brno, Czech Republic},
  url = {https://publik.tuwien.ac.at/files/publik_270279.pdf},
  doi = {10.2312/eurp.20181120},
}