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The application of visual analytics to financial stability monitoring
Institution:1. Office of Financial Research, 717 14th Street, NW, Washington, DC 20005, USA;2. Media and Graphic Interdisciplinary Centre, University of British Columbia, Forest Sciences Centre Building, FSC 3640 – 2424 Main Mall, Vancouver, BC, Canada V6T 1Z4;3. Old Road Campus Research Building, Old Road Campus, University of Oxford, Roosevelt Drive, Oxford OX3 7DQ, UK;4. Human-Computer Interaction and Head Interaction Design Centre, School of Science and Technology, Middlesex University London, The Burroughs, Hendon, London NW4 4BT, UK;1. Università Cattolica, largo Gemelli 1, 20123 Milano, Italy;2. Bocconi University, via Roentgen 1, 20136 Milano, Italy;1. School of Technology, University of Campinas, R. Paschoal Marmo, 1888, Jardim Nova, Itália, Limeira, SP, CEP 13484-332, Brazil;2. Institute of Computing, University of Campinas, Av. Albert Einstein, 1251, Cidade, Universitria, Campinas, SP, CEP 13083-852, Brazil;3. Scylla Bioinformática, Rua Francisco Otaviano, 60, Sala 22, Jardim Chapadão, Campinas, SP, CEP 13070-056, Brazil;4. AREMAS, Rua Regente Feijó, 121, Sala 92, Centro, Campinas, SP, Brazil;5. AES-Tietê, Bauru, SP, Brazil;1. Department of Economics, City University London, Social Sciences Building, Northampton Square, London EC1V 0HB, UK;2. Department of Economics, City University London and Department d’Economia Aplicada, Universitat Autònoma de Barcelona, Edifici B Campus de la UAB, Cerdanyola del Vallès, 08193, Barcelona, Spain;1. Board of Governors of the Federal Reserve System, United States;2. Federal Reserve Bank of Chicago, United States
Abstract:This paper provides an overview of visual analytics—the science of analytical reasoning enhanced by interactive visualizations tightly coupled with data analytics software—and discusses its potential benefits in monitoring systemic financial stability. The core strength of visual analytics is to combine visualization's high-bandwidth information channel to the human analyst with the flexibility and power of rapid-iteration analytics. This combination is especially valuable in the context of macroprudential supervision, which is increasingly dominated by large volumes of dynamic and heterogeneous data. Our contribution is to describe and categorize the analytical challenges faced by macroprudential supervisors, and to indicate where and how visual analytics can increase supervisors’ comprehension of the data stream, helping to transform it into actionable knowledge to support informed decision- and policy-making. The paper concludes with suggestions for a research agenda.
Keywords:Financial stability  Macroprudential supervision  Monitoring  Systemic risk  Visual analytics
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