Privacy-Preserving Methods for Sharing Financial Risk Exposures

28 Pages Posted: 20 Nov 2011 Last revised: 25 Nov 2011

See all articles by Emmanuel A. Abbe

Emmanuel A. Abbe

École Polytechnique Fédérale de Lausanne (EPFL)

Amir Khandani

Massachusetts Institute of Technology (MIT)

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering

Date Written: November 19, 2011

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.

Keywords: Systemic Risk, Risk Management, Financial Crisis, Cryptography, Security Multi-Party Computation

JEL Classification: G12, G14, C70, D70, D82, L50

Suggested Citation

Abbe, Emmanuel A. and Khandani, Amir E. and Lo, Andrew W., Privacy-Preserving Methods for Sharing Financial Risk Exposures (November 19, 2011). Available at SSRN: https://ssrn.com/abstract=1962090 or http://dx.doi.org/10.2139/ssrn.1962090

Emmanuel A. Abbe

École Polytechnique Fédérale de Lausanne (EPFL) ( email )

Station 5
Odyssea 1.04
1015 Lausanne, CH-1015
Switzerland

HOME PAGE: http://ipg.epfl.ch/~eabbe

Amir E. Khandani

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Laboratory for Financial Engineering ( email )

100 Main Street
E62-618
Cambridge, MA 02142
United States
617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

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