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Privacy-Preserving Methods for Sharing Financial Risk Exposures

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

Abstract

Unlike other industries in which intellectual property is patentable, 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. We develop methods for sharing and aggregating such risk exposures that protect the privacy of all parties involved and without the need for a trusted third party. Our approach employs secure multi-party computation techniques from cryptography in which multiple parties are able to compute joint functions without revealing their individual inputs. In our framework, individual financial institutions evaluate a protocol on their proprietary data which cannot be inverted, leading to secure computations of real-valued statistics such a concentration indexes, pairwise correlations, and other single- and multi-point statistics. The proposed protocols are computationally tractable on realistic sample sizes. Potential financial applications include: the construction of privacy-preserving real-time indexes of bank capital and leverage ratios; the monitoring of delegated portfolio investments; financial audits; and the publication of new indexes of proprietary trading strategies.

Suggested Citation

  • Emmanuel A. Abbe & Amir E. Khandani & Andrew W. Lo, 2011. "Privacy-Preserving Methods for Sharing Financial Risk Exposures," Papers 1111.5228, arXiv.org, revised Nov 2011.
  • Handle: RePEc:arx:papers:1111.5228
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    Cited by:

    1. Ho Hwang, Jong, 2013. "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.
    2. Kasinger, Johannes & Pelizzon, Loriana, 2018. "Financial stability in the EU: A case for micro data transparency," SAFE Policy Letters 67, Goethe University Frankfurt, Research Center SAFE - Sustainable Architecture for Finance in Europe.
    3. 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.
    4. Mark Flood & Jonathan Katz & Stephen Ong & Adam Smith, 2013. "Cryptography and the Economics of Supervisory Information: Balancing Transparency and Confidentiality," Working Papers 13-08, Office of Financial Research, US Department of the Treasury.

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