This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1073/pnas.2537388123. This is version 2 of this Preprint.
FEMA Phase-Out? Catastrophic Extremes Limit Decentralization of U.S. Flood Insurance
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Abstract
The U.S. National Flood Insurance Program (NFIP) faces growing solvency and affordability challenges amid proposals to decentralize the Federal Emergency Management Agency (FEMA) and shift disaster management to states. Catastrophic floods often span state boundaries, exposing multiple decentralized insurance pools simultaneously. Using a path-independent simulation framework that integrates risk-based premiums, hydrometeorologically clustered flood losses, and 2025 reinsurance contracts, we evaluate the stability of national and state-level pooling using historical data. National pooling markedly reduces systemic insolvency through cross-regional diversification, while many state pools exhibit structural fragility. State-level deficits are dominated by hyperclusters—coherent spatiotemporal losses induced by common atmospheric drivers—indicating that clustered loss governs failure. Since states must balance budgets and face borrowing restrictions to cover large losses, pool liquidity constrains decentralized systems. Existing reinsurance (including insurance-linked securities) does not always cover these clustered losses due to its misalignment with the clustered, spatiotemporal nature of hydroclimatic risk, covering only single flood events in traditional contracts and individual named storms in FloodSmart catastrophe bonds. A resilient and affordable NFIP will require hybrid financial design aligning risk-based premiums and reinsurance to balance chronic and catastrophic risk.
DOI
https://doi.org/10.31223/X56178
Subjects
Applied Statistics, Climate, Hydrology, Meteorology, Natural Resources Management and Policy, Risk Analysis, Sustainability, Systems Engineering
Keywords
risk management, natural disasters, Flood Insurance, Reinsurance, hydroclimate, machine learning, Game theory, systems modeling
Dates
Published: 2025-11-13 10:19
Last Updated: 2026-08-19 09:33
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License
CC BY Attribution 4.0 International
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