Privacy-Preserving Network Analytics

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See all articles by Marcella Hastings

Marcella Hastings

affiliation not provided to SSRN

Brett Hemenway Falk

University of Pennsylvania - Department of Computer and Information Science

Gerry Tsoukalas

University of Pennsylvania - The Wharton School

Date Written: August 24, 2020

Abstract

Using financial networks as a backdrop, we develop a new framework for privacy-preserving network analytics. Adopting the debt and equity models of Eisenberg and Noe (2001) and Elliott et al. (2014) as proof of concept, we show how aggregate-level statistics required for stress testing and stability assessment can be derived on real network data, without any individual node revealing its private information to any third party, be it other nodes in the network, or even a central agent. Our work helps bridge the gap between the theoretical models of financial networks that assume agents have full information, and the real world, where information sharing is hindered by privacy and security concerns.

Keywords: financial networks, multiparty computation, privacy preservation, fintech

JEL Classification: E6, G2, L5, O3, C6

Suggested Citation

Hastings, Marcella and Hemenway Falk, Brett and Tsoukalas, Gerry, Privacy-Preserving Network Analytics (August 24, 2020). Available at SSRN: https://ssrn.com/abstract=

Marcella Hastings

affiliation not provided to SSRN

Brett Hemenway Falk

University of Pennsylvania - Department of Computer and Information Science ( email )

3330 Walnut Street
Philadelphia, PA 19104
United States

Gerry Tsoukalas (Contact Author)

University of Pennsylvania - The Wharton School ( email )

3641 Locust Walk
Philadelphia, PA 19104-6365
United States

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