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

Runhuan Feng (), Chongda Liu () and Stephen Taylor ()
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Runhuan Feng: University of Illinois
Chongda Liu: University of Illinois
Stephen Taylor: New Jersey Institute of Technology

Annals of Operations Research, 2023, vol. 321, issue 1, No 28, 813-842

Abstract: 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.

Keywords: Peer-to-peer insurance; Risk sharing; Pareto optimality (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-022-04841-x

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