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Big data challenges and opportunities in financial stability monitoring

Author

Listed:
  • Flood, M. D.
  • Jagadish, H. V.
  • Raschid, L.

Abstract

The exponential growth of machine-readable data to record and communicate activities throughout the financial system has significant implications for macroprudential monitoring. The central challenge is the scalability of institutions and processes in the face of the variety, volume, and rate of the “big data” deluge. This deluge also provides opportunities in the form of new, rapidly available, valuable streams of information with finer levels of detail and granularity. A difference in scale can become a difference in kind, as legacy processes are overwhelmed and innovative responses emerge.Despite the importance and ubiquity of data in financial markets, processes to manage this crucial resource must adapt. This need applies especially to financial stability or macroprudential analysis, where information must be assembled, cleaned, and integrated from regulators around the world to build a coherent view of the financial system to support policy decisions. We consider the key challenges for systemic risk supervision from the expanding volume and diversity of financial data. The discussion is organised around five broad supervisory tasks in the typical life cycle of supervisory data.

Suggested Citation

  • Flood, M. D. & Jagadish, H. V. & Raschid, L., 2016. "Big data challenges and opportunities in financial stability monitoring," Financial Stability Review, Banque de France, issue 20, pages 129-142, April.
    • Handle: RePEc:bfr:fisrev:2016:20:14
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    1. Office of Financial Research (ed.), 2016. "2016 Financial Stability Report," Reports, Office of Financial Research, US Department of the Treasury, number 16-3, May.
    2. Goodell, John W. & Kumar, Satish & Lim, Weng Marc & Pattnaik, Debidutta, 2021. "Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).
    3. Ka Kei Chan & Alistair Milne, 2019. "The Global Legal Entity Identifier System: How Can It Deliver?," JRFM, MDPI, vol. 12(1), pages 1-29, March.
    4. Zhao, Yang & Goodell, John W. & Wang, Yong & Abedin, Mohammad Zoynul, 2023. "Fintech, macroprudential policies and bank risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 87(C).

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