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Privacy-Preserving Methods for Sharing Financial Risk Exposures

Author

Listed:
  • Emmanuel A. Abbe
  • Amir E. Khandani
  • Andrew W. Lo

Abstract

The financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. Using results from cryptography, we develop computationally tractable protocols for sharing and aggregating such risk exposures that protect the privacy of all parties involved, without the need for trusted third parties. Financial institutions can share aggregate statistics such as Herfindahl indexes, variances, and correlations without revealing proprietary data. Potential applications include: privacy-preserving real-time indexes of bank capital and leverage ratios; monitoring delegated portfolio investments; financial audits; and public indexes of proprietary trading strategies.

Suggested Citation

  • Emmanuel A. Abbe & Amir E. Khandani & Andrew W. Lo, 2012. "Privacy-Preserving Methods for Sharing Financial Risk Exposures," American Economic Review, American Economic Association, vol. 102(3), pages 65-70, May.
    • Handle: RePEc:aea:aecrev:v:102:y:2012:i:3:p:65-70
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    File URL: http://www.aeaweb.org/articles.php?doi=10.1257/aer.102.3.65
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    Cited by:

    1. Daniel Goroff & Jules Polonetsky & Omer Tene, 2018. "Privacy Protective Research: Facilitating Ethically Responsible Access to Administrative Data," The ANNALS of the American Academy of Political and Social Science, , vol. 675(1), pages 46-66, January.
    2. Dimitrios Bisias & Mark Flood & Andrew W. Lo & Stavros Valavanis, 2012. "A Survey of Systemic Risk Analytics," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 255-296, October.
    3. Taylor Reynolds & Sarah Scheffler & Daniel J. Weitzner & Angelina Wu, 2024. "Mind the Gap: Securely modeling cyber risk based on security deviations from a peer group," Papers 2402.04166, arXiv.org.
    4. David Cerezo S'anchez, 2021. "JUBILEE: Secure Debt Relief and Forgiveness," Papers 2109.07267, arXiv.org.
    5. Wang, Yi-Ran & Ma, Chao-Qun & Ren, Yi-Shuai, 2022. "A model for CBDC audits based on blockchain technology: Learning from the DCEP," Research in International Business and Finance, Elsevier, vol. 63(C).
    6. Mark D. Flood & Jonathan Katz & Stephen J. Ong & Adam Smith, 2013. "Cryptography and the economics of supervisory information: balancing transparency and confidentiality," Working Papers (Old Series) 1312, Federal Reserve Bank of Cleveland.
    7. Douglas J. Elliott & Greg Feldberg & Andreas Lehnert, 2013. "The History of Cyclical Macroprudential Policy in the United States," Working Papers 13-08, Office of Financial Research, US Department of the Treasury.
    8. Kasinger, Johannes & Pelizzon, Loriana, 2018. "Financial stability in the EU: A case for micro data transparency," SAFE Policy Letters 67, Leibniz Institute for Financial Research SAFE.
    9. Roukny, Tarik & Battiston, Stefano & Stiglitz, Joseph E., 2018. "Interconnectedness as a source of uncertainty in systemic risk," Journal of Financial Stability, Elsevier, vol. 35(C), pages 93-106.
    10. Ho Hwang, Jong, 2014. "A proposal for an open-source financial risk model," LSE Research Online Documents on Economics 59298, London School of Economics and Political Science, LSE Library.
    11. Ning Cai & Steven Kou, 2019. "Econometrics with Privacy Preservation," Operations Research, INFORMS, vol. 67(4), pages 905-926, July.

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