Moody's: Uninsured US Flood Losses Could Exceed $1 Trillion in Extreme Scenarios

US counties face approximately $375 billion in aggregate uninsured residential flood loss exposure under a modeled 1-in-100-year flood scenario, while losses could exceed $1 trillion in more severe events, according to new analysis, "US exposed to $375 billion–$1 trillion in aggregated uninsured flood losses from a range of extreme events," from Moody's.

The research highlights persistent flood insurance protection gaps across much of the country and suggests that expanding flood exposure could increase financial pressure on households, local governments, and state budgets. Moody's said residential flood exposure poses growing credit risks because of rising insurance costs, potential declines in property values, and increasing demands for climate-resilient infrastructure investment.

The analysis examined residential flood exposure using Moody's RMS US Inland Flood HD model under three scenarios: a 1-in-100-year flood event, a more severe 1-in-500-year flood event, and a 2050 intermediate-emissions climate scenario. All scenarios assume current insurance participation remains unchanged and do not account for additional flood mitigation investments.

Under the baseline 1-in-100-year flood scenario, aggregate uninsured residential flood loss exposure exceeds $375 billion nationwide, with an estimated insurance protection gap of approximately 65 percent. While flood exposure is widespread, the largest potential uninsured losses are concentrated in a relatively small number of locations.

Counties with more than $5 billion in potential uninsured losses are concentrated in Florida, Louisiana, South Carolina, and Texas. Moody's noted that all four states have moderate-to-high credit exposure to physical climate risk.

At the same time, flood exposure extends far beyond those areas. Approximately 90 percent of US counties face some level of flood risk and generally exhibit significant insurance protection gaps. Most of those counties have relatively modest potential uninsured losses of $150 million or less, but Moody's found that the cumulative exposure remains substantial nationwide.

The analysis also found that uninsured flood losses are highly concentrated. Less than 2 percent of counties account for roughly 65 percent of aggregate uninsured loss exposure under the 1-in-100-year scenario, while counties with more than $1 billion in potential uninsured losses are spread across 11 states.

The financial exposure increases significantly under more severe flood scenarios. In a modeled 1-in-500-year event, nationwide uninsured loss exposure could exceed $1 trillion, while the insurance protection gap rises above 70 percent, according to Moody's.

Under that scenario, counties with more than $5 billion in potential uninsured losses would expand beyond the Gulf Coast and Atlantic Coast into 11 states, including California, Connecticut, Georgia, Illinois, New Jersey, New York, and Pennsylvania. Some of those states currently have relatively low exposure to physical climate risk, illustrating how extreme events can broaden the geographic footprint of flood losses.

The concentration of losses also becomes more pronounced in severe events. Moody's estimates that counties with more than $1 billion in uninsured losses would account for approximately 80 percent of aggregate exposure in the 1-in-500-year scenario, compared with 65 percent in the baseline scenario.

Looking further ahead, the analysis examined a 2050 intermediate-emissions climate scenario and found that aggregate uninsured flood loss exposure could increase by approximately 25 percent, reaching around $472 billion. The nationwide protection gap remains near 65 percent, suggesting that rising flood hazards alone could increase financial exposure even if insurance participation remains unchanged.

In that future-climate scenario, counties with more than $5 billion in uninsured losses would expand into New Jersey while remaining concentrated in Florida, Louisiana, South Carolina, and Texas. Counties with more than $1 billion in uninsured losses would account for approximately 70 percent of aggregate nationwide exposure.

A key finding of the research is the persistence of the flood insurance protection gap. Moody's compared residential properties exposed to flooding with properties carrying National Flood Insurance Program (NFIP) coverage and found significant differences between economic exposure and insured exposure. The analysis concludes that uninsured losses stem from a continuing mismatch between expanding flood hazards and insurance participation.

Flood insurance take-up rates remain low even in many of the nation's highest-risk areas. Along portions of the Gulf Coast and Eastern Seaboard, participation generally ranges between 10 and 30 percent, according to Moody's. The result is that a significant portion of recovery costs may ultimately fall on households, local governments, state governments, and federal disaster assistance programs.

The analysis also points to limitations in Federal Emergency Management Agency (FEMA) flood maps as a contributor to the protection gap. FEMA's Special Flood Hazard Area maps primarily focus on riverine flooding and may not fully capture risks associated with extreme precipitation, storm surge, sea-level rise, and other flood drivers. Moody's noted that meaningful flood exposure and losses can occur outside FEMA-designated flood zones.

While private flood insurance has expanded in recent years, the NFIP remains the dominant source of residential flood coverage. Moody's found that private policies account for roughly 10 percent of total policies in force, while declines in NFIP policies have largely offset growth in the private market, leaving the overall protection gap largely unchanged.

The research highlighted Hurricane Helene as an example of how extreme weather events can exceed historical expectations. Severe flooding in Asheville and Buncombe County, North Carolina, during September 2024 followed rainfall that exceeded the 1-in-1,000-year rainfall return period, according to the analysis.

Moody's noted that Buncombe County faced financial pressures following the storm and cited its own rating actions on the county during the recovery period. Despite the elevated flood risk, modeled results indicate a flood insurance protection gap of approximately 88 percent across multiple flood severity scenarios.

The analysis also examined uninsured loss exposure relative to property replacement costs. Moody's found that counties with the largest absolute uninsured losses do not necessarily have the highest uninsured loss exposure ratios, meaning smaller losses can still represent significant financial strain for individual communities depending on the size of their residential property base.

Under the baseline scenario, most counties have uninsured loss exposure ratios below 1 percent of replacement costs. However, counties in Florida, Kentucky, Louisiana, South Dakota, South Carolina, and Texas were identified as having uninsured loss exposure ratios exceeding 10 percent, indicating heightened vulnerability to severe flood events.

Moody's concluded that the ultimate credit impact of flooding depends not only on the size of uninsured losses but also on a community's ability to absorb and recover from those losses. Factors such as federal disaster assistance, local reserves, liquidity, governance practices, infrastructure resilience, and broader risk management efforts can all influence long-term financial outcomes.