Peer-to-peer risk sharing with an application to flood risk pooling

Runhuan Feng, Chongda Liu, Stephen Taylor

Research output: Contribution to journalArticlepeer-review

Abstract

With the rise of decentralized finance and insurance technology, there has been growing interest in the financial industry for risk sharing mechanisms without a central authority or clearing house. In contrast with classic centralized risk sharing, a novel peer-to-peer risk sharing framework is proposed. The presented framework aims to devise a risk allocation mechanism that is structurally decentralized, Pareto optimal, and mathematically fair. An explicit form for the pool allocation ratio matrix is derived, and convex programming techniques are applied to determine the optimal pooling mechanism in a constrained variance reduction setting. A tiered hierarchical generalization is also constructed to improve computational efficiency. As an illustration, these techniques are applied to a flood risk pooling example. Flood risk is known to be difficult to cover in practice, which contributes to the stagnant development for a private insurance market. It is shown in this paper that peer-to-peer risk sharing techniques provide an economically viable alternative to traditional flood insurance policies.

Original languageEnglish (US)
Pages (from-to)813-842
Number of pages30
JournalAnnals of Operations Research
Volume321
Issue number1-2
DOIs
StatePublished - Feb 2023

Keywords

  • Pareto optimality
  • Peer-to-peer insurance
  • Risk sharing

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Management Science and Operations Research

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