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The Application of Visual Analytics to Financial Stability Monitoring

Author

Listed:
  • Mark D. Flood

    (Office of Financial Research)

  • Victoria L. Lemieux

    (University of British Columbia)

  • Margaret Varga

    (University of Oxford)

  • B.L. William Wong

    (Middlesex University)

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. Macroprudential supervisors face a daunting challenge with at least three facets of the financial system. First, the financial system is complex, enormous, highly diverse, and constantly changing. Second, the set of financial and econometric models proposed to help comprehend threats to financial stability is large, diverse, and growing. Third, certain regulatory activities, such as rulemaking and decision-making, generate special requirements for transparency and accountability that can complicate or restrict the choices of tools and approaches. This paper explores these challenges in the context of visual analytics. Visual analytics can increase supervisors' comprehension of the data stream, helping to transform it into actionable knowledge to support decision- and policy-making. The paper concludes with suggestions for a research agenda.

Suggested Citation

  • Mark D. Flood & Victoria L. Lemieux & Margaret Varga & B.L. William Wong, 2014. "The Application of Visual Analytics to Financial Stability Monitoring," Working Papers 14-02, Office of Financial Research, US Department of the Treasury, revised 07 Oct 2014.
    • Handle: RePEc:ofr:wpaper:14-02
    as

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    References listed on IDEAS

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    Cited by:

    1. Aikman, David & Kiley, Michael & Lee, Seung Jung & Palumbo, Michael G. & Warusawitharana, Missaka, 2017. "Mapping heat in the U.S. financial system," Journal of Banking & Finance, Elsevier, vol. 81(C), pages 36-64.
    2. Lang, Jan Hannes & Peltonen, Tuomas A. & Sarlin, Peter, 2018. "A framework for early-warning modeling with an application to banks," Working Paper Series 2182, European Central Bank.
    3. Cwynar Andrzej & Cwynar Wiktor & Pater Robert & Kaźmierkiewicz Piotr, 2017. "Information needs of financial market professionals in the big data and social media era. The empirical evidence from Poland," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 13(4), pages 1-13, December.
    4. Flood, Mark D. & Lemieux, Victoria L. & Varga, Margaret & William Wong, B.L., 2016. "The application of visual analytics to financial stability monitoring," Journal of Financial Stability, Elsevier, vol. 27(C), pages 180-197.
    5. Lusardi, Annamaria & Samek, Anya & Kapteyn, Arie & Glinert, Lewis & Hung, Angela & Heinberg, Aileen, 2017. "Visual tools and narratives: new ways to improve financial literacy," Journal of Pension Economics and Finance, Cambridge University Press, vol. 16(3), pages 297-323, July.
    6. Ajit Desai & Jacob Sharples & Anneke Kosse, 2024. "Finding a needle in a haystack: a machine learning framework for anomaly detection in payment systems," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Granular data: new horizons and challenges, volume 61, Bank for International Settlements.
    7. Constantin Zopounidis & Michalis Doumpos & Dimitrios Niklis, 2018. "Financial decision support: an overview of developments and recent trends," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 63-76, June.
    8. Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
    9. Zhibin Niu & Runlin Li & Junqi Wu & Dawei Cheng & Jiawan Zhang, 2020. "iConViz: Interactive Visual Exploration of the Default Contagion Risk of Networked-Guarantee Loans," Papers 2006.09542, arXiv.org, revised Aug 2020.
    10. Stanley Fischer, 2015. "Financial Stability and Shadow Banks: What We Don't Know Could Hurt Us: a speech at the \"Financial Stability: Policy Analysis and Data Needs\" 2015 Financial Stability Conference sponsored ," Speech 885, Board of Governors of the Federal Reserve System (U.S.).
    11. Irving Fisher Committee, 2024. "Granular data: new horizons and challenges," IFC Bulletins, Bank for International Settlements, number 61.
    12. Mark E. Paddrik & Richard Haynes & Andrew E. Todd & William T. Scherer & Peter A. Beling, 2016. "Visual analysis to support regulators in electronic order book markets," Environment Systems and Decisions, Springer, vol. 36(2), pages 167-182, June.
    13. Bholat, David & Broughton, Nida & Ter Meer, Janna & Walczak, Eryk, 2019. "Enhancing central bank communications using simple and relatable information," Journal of Monetary Economics, Elsevier, vol. 108(C), pages 1-15.
    14. Kinsella, Stephen, 2019. "Visualising economic crises using accounting models," Accounting, Organizations and Society, Elsevier, vol. 75(C), pages 1-16.
    15. Sophie Cockcroft & Mark Russell, 2018. "Big Data Opportunities for Accounting and Finance Practice and Research," Australian Accounting Review, CPA Australia, vol. 28(3), pages 323-333, September.
    16. Bholat, David, 2015. "Big data and central banks," Bank of England Quarterly Bulletin, Bank of England, vol. 55(1), pages 86-93.

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    Keywords

    Financial stability; macroprudential supervision; monitoring; systemic risk; visual analytics;
    All these keywords.

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