Key takeaways
- UK flood risk protection gap is narrow now because insurance penetration is high.
- Fiscal risks are limited at present but could become material in extreme events.
- Flood Re and flood defences support coverage, but both face strains as flood risk rises.
- Some concentration of economic risk in rural areas in Wales.
- Adaptation investment can help preserve resilien
Natural catastrophe insurance protection gaps can weaken government credit quality by shifting losses on to public sector balance sheets, disrupting economic activity and revenue, and increasing contingent liabilities as governments typically act as last providers of support to affected communities.
In the UK, the country-wide flood insurance protection gap is relatively narrow at around 10% of total economic losses. Flood Re, a joint government and industry reinsurance scheme, plays a key role in improving affordability for households in high-risk areas and supporting residential coverage.
However, Flood Re’s costs are growing, as claims increase in size and frequency. Over time, rising flood risk, including expanding exposure in flood-prone areas, tighter reinsurance conditions and Flood Re’s scheduled closure in 2039 could widen protection gaps and shift more losses on to the UK public sector.
In this analysis, Moody’s defines the insurance protection gap as the portion of total economic losses that are uninsured. Moody’s measure of economic losses covers only insurable property assets — including residential, commercial, industrial and agriculture property, and motor vehicles — and excludes damage to infrastructure, the natural environment and agricultural crops, which can account for a significant share of the wider economy-wide protection gap.
Uninsured losses can erode government credit quality
Protection gaps are credit relevant for both sovereigns and regional and local governments.
Severe weather events weaken economic activity, disrupting output, investment and supply chains, and eroding tax revenue — just as demands on government spending are rising. Insurance facilitates faster mobilisation of private capital. When that coverage is limited, recovery is slower and pressure for government support to households and businesses is larger, prolonging the drag on economic growth and fiscal performance.
While typically wider in emerging markets with lower insurance penetration, protection gaps are material even in advanced economies, as highlighted in Moody’s US flood study , which found the country was exposed to $375 billion to $1 trillion in aggregated uninsured flood losses from a range of extreme events.
The mechanics of risk transfer to the public sector are illustrated well by Germany’s 2021 floods . Relatively low insurance coverage for buildings — around 47% in Nordrhein Westfalen and 37% in Rheinland Pfalz — shifted substantial costs on to the public sector, prompting the creation of a €30 billion reconstruction fund jointly financed by the federal government and the Länder (states).
Over time, repeated events can raise baseline spending, weaken revenue and reduce fiscal flexibility. In more exposed countries, they push up risk premiums and borrowing costs. The scale of the credit impact depends not only on physical exposure but also on fiscal buffers, institutions and governance strength and the effectiveness of adaptation.
In Pakistan’s 2022 floods, weak institutions and governance strength added to uncertainty over whether the country could maintain a credible policy path after the natural catastrophe, which caused losses of around 10% of GDP, sharply weakened growth, raised inflation and widened the fiscal deficit by several percentage points.
UK flood exposure is material, but insurance coverage is strong
The UK’s Climate Change Committee estimates that around 7 million properties (residential and non-residential) were at risk of flooding in 2025, rising 40% by 2050 under a Paris-aligned climate scenario .
The 2007 summer floods caused £4.8 billion of economic damage in 2025 prices (0.2% of GDP), according to the Office for Budget Responsibility (OBR) . Moody’s Analytics and Flood Re joint research suggests this was a 1-in-30 to 1-in-45 year loss event. Of the total, £3.1 billion related to damage to homes, businesses and vehicles, £0.7 billion to utilities, and £0.9 billion to infrastructure and public health. The OBR estimated that government covered around half of utility damage and all infrastructure and public health costs, implying a direct fiscal cost of £1.3 billion, or 27% of the total and 40% of property damage.
It also estimated that direct fiscal costs from the 2015-16 floods were equal to around 66% of property-related losses, or 36% of total economic costs.
When the 2007 floods hit, the state picked up a big share
The OBR put the 2007 England summer floods at about £4.8 billion in today's prices. Switch from the damage by sector to who ultimately paid: the government met all infrastructure and public-health costs and around half of utility damage — a direct fiscal hit of roughly £1.3 billion.
The OBR does not estimate the uninsured share of total property damage. Based on Moody’s data, average annual uninsured property losses are low, and below £100 million. Much higher losses are possible, but rare.
Uninsured flood losses have a 1% chance of exceeding £1.1 billion in any given year (1-in-100 year return period), and a 0.2% chance of exceeding £2.3 billion in any given year (1-in-500 return period), according to Moody’s data. These figures refer to total losses over an entire year, rather than a single flood event, reflecting that the UK often experiences multiple floods within the same year.
What stays uninsured when the UK floods?
The protection gap — the share of flood losses that are uninsured — holds at roughly one-tenth of the total, but in absolute terms it climbs into the billions in rare, severe flood years.
Despite this exposure, the property-related flood protection gap remains relatively narrow at around 10% across many return periods. Household insurance penetration is high, supported by mortgage requirements and Flood Re, which improves the availability and affordability of cover for most eligible residential properties. Commercial flood cover is also usually maintained because lenders, leases and counterparties often require it, even when premiums are high.
In an intermediate emissions scenario such as Representative Concentration Pathway (RCP) 4.5, annual 1-in-100 year uninsured flood losses would rise by around 30% compared to today’s climate, while the protection gap would remain broadly unchanged at about 10%. However, this is on a ground-up basis under today’s policy terms. Insurers could respond to higher expected losses by raising deductibles or lowering policy limits, increasing policyholder loss retention.
A more extreme RCP scenario would also increase both average losses and tail risk, especially in more severe scenarios. At the same time, higher losses would likely trigger more investment in flood defences.
How a higher emissions scenario could impact flood losses
Compare a severe UK flood year in today’s climate with the same year under an intermediate-warming (RCP 4.5) 2050 scenario, at the 1-in-100 and 1-in-500 uninsured loss level.
Flood Re stability is under pressure
Flood Re is a UK single-peril reinsurance scheme created under the Water Act 2014 to keep household flood insurance available and affordable while supporting a transition to risk-reflective pricing by 2039, enabled by simultaneous government investment in flood defences. Households still buy insurance from private insurers, which can cede the flood element of eligible policies to Flood Re. The scheme covers private households only. It does not cover commercial or other property, public infrastructure, homes built after 2009 or other natural catastrophe perils such as windstorm, drought and coastal erosion. As such, economy-wide uninsured losses can remain material even if household flood cover is relatively strong.
The UK model is less centralised than the main public flood schemes in France, Spain and the US. In Spain, the Consorcio directly compensates extraordinary-risk claims. In France, Cat Nat is embedded in standard property insurance, with insurers paying claims and transferring risk through state-backed reinsurance. In the US, the National Flood Insurance Program (NFIP) acts as a primary government insurer and is only required when obtaining federally backed mortgages for properties lying on the Federal Emergency Management Agency’s (FEMA) flood zones.
Funding also differs: Flood Re relies on a £160 million annual industry levy and fixed premiums, while France uses a broader surcharge across property policies backed by unlimited state-supported reinsurance. The NFIP has Treasury borrowing capacity but has built up substantial debt.
How Flood Re compares with other public flood schemes
The UK model is less centralised than the public catastrophe schemes in France, Spain and the US — with different perils, funding and degrees of state backing.
Pressure on Flood Re is rising. In 2024-25, 346,200 policies were ceded to the scheme, up 20% year on year and the highest level since inception. More frequent and higher-value claims have increased annual reinsurance costs by £100 million, while net retention for the 2025-28 cycle has risen to £347 million from £130 million in the 2022-25 programme.
Flood Re has responded by raising the insurer levy to £160 million from £135 million, increasing the statutory loss limit to £250 million from £100 million, and lifting the reinsurance liability limit to £3.2 billion from £2.1 billion from April 2025. These steps strengthen the resilience of Flood Re now but may not be sufficient to keep up with the possible increase in claims between now and 2039.
Flood Re’s safety buffers have been cranked right up
Climbing claims and pricier reinsurance have forced Flood Re to absorb far more risk.
Risks for the UK public sector are manageable now
But will rise over the medium term
The modelled flood insurance protection gap implies a very small drag on UK nominal output. However, layering on the impact of damage to public utilities and infrastructure public health costs and disaster relief funding would raise direct fiscal costs. Combining Moody’s modelled losses with the OBR’s analysis of the fiscal share of previous UK flood events, Moody’s estimates that the direct fiscal costs of a 1-in-100 year flood year could be equivalent to about 0.2% of UK GDP, roughly doubling to around 0.4% of GDP in a 1-in-500 year scenario.
That said, the UK’s large, diversified economy and strong institutions mean that even a severe flood event is unlikely to create immediate fiscal stress. The key credit risk is cumulative: repeated disaster-related spending, often unplanned and difficult to defer, can gradually put pressure on public finances if it rises faster than GDP, while flood-related disruption can weaken tax receipts and local economic activity. Additional indirect strains can arise from political pressure for support on uninsured losses.
Tighter reinsurance conditions, insurance protection gaps in parts of the economy and the planned closure of Flood Re in 2039 will all increase risks over the longer term if resilience measures do not keep pace. The closure of Flood Re could cause housing market spillovers if the costs of insurance rise materially, leading to a larger insurance protection gap, a tightening in mortgage access and falls in property values in high-risk areas.
At the sub-national level, losses and protection gaps are also low, although there is some concentration in rural Wales
Moody’s looked at uninsured losses at the sub-national level through two different lenses: as a percentage of the total economic value of property in a local area and as a percentage of local economic output (gross value added/GVA).
How exposed is your patch of Britain?
See the uninsured flood protection gap across UK local authorities — with Greater London shown as a single area — through two lenses, at a relatively infrequent 1-in-100-year level of losses or an extremely rare 1-in-500-year scenario.
Uninsured losses as a percentage of total economic value in every sub-national area in the UK are low and well below 1% even in a 1-in-500 return period. But, despite low relative exposure levels, there is significant variation – with some areas facing risk levels that are many times higher than others.
Looking at uninsured losses as a percentage of local economic outputs, there is some concentration in rural areas in England, Wales and Scotland. Five of the 10 most exposed local authorities are in Wales. The Welsh county boroughs of Merthyr Tydfil and Rhondda Cynon Taff, and the English county of Derbyshire have the highest uninsured losses compared to the size of their local economies, at many times the national level.
The concentration in Welsh rural areas reflects comparatively high rainfall , steep valley topography in which rivers flow rapidly during heavy rain, weaker flood defences in some areas and historical development patterns whereby towns developed along valley floors, placing housing and infrastructure in natural flood plains. In addition, Welsh local authorities have lower GVA than their English counterparts.
Moody’s has also analysed uninsured losses as a percentage of local government budgets – but this is highly variable. In some areas, uninsured losses in a 1-in-100 year flood loss scenario would exceed entire local government budgets. However, the key driver here is small local government budgets compared to flood exposure. It highlights that UK government support would be essential for recovery, and the key role that pre-event resilience investment can play.
Precedent suggests that the UK government does usually reimburse local authorities for much of the cost of emergency response, clean-up and immediate recovery. This support is mainly provided through the Bellwin Scheme, which can be activated in exceptional emergencies and covers part of the immediate response costs incurred by local authorities. Authorities must still absorb spending up to a specified threshold, typically a small share of their annual budget, with only costs above that level eligible for reimbursement. After major floods, additional cross-government funding has also helped pay for some repairs to highways, schools and other public services.
Even so, local authorities are still likely to bear part of the rebuilding cost, because the wider funding model is based on shared responsibility and any central government support beyond the immediate response phase is discretionary. In the example of the 2007 floods, the OBR estimated that local authorities paid about £202 million, or around 4% of the whole economy cost of the floods.
Sizeable adaptation programme focuses on flood defences
The UK’s existing flood defence network materially limits losses, and supports our view of its low exposure to physical climate risk, but its effective standard of protection will decline over time as flood severity increases. A Moody’s/Flood Re case study suggests that even in relatively well protected areas, more severe emissions scenarios could generate material additional losses by 2040 unless defences are strengthened.
While higher defence standards can mitigate this increase, returns diminish because hard defences do not address all sources of flooding, particularly surface water. This indicates that further adaptation will need to extend beyond traditional defences to include broader resilience measures, such as property level protection and improved surface water management. Strengthening resilience will also be key to sustaining insurance availability and affordability, particularly in higher risk areas, as Flood Re approaches closure.
Evidence from the Climate Change Committee indicates that adaptation delivery is not keeping pace with the rising frequency and severity of flood events. The committee estimates that around £1.6 billion to £2.2 billion per year is required for flood risk management to 2050 to offset increasing hazard, and around £11 billion annually across the economy for overall adaptation. These requirements suggest that the UK’s current programme , including the £10.5 billion earmarked for flood defences and coastal protection over 2024-36, may be insufficient to prevent a gradual erosion of resilience as flood risks intensify.
Unlike mitigation, adaptation investment is largely non revenue generating, focusing instead on avoided losses. Related costs are therefore likely to fall predominantly on the public sector balance sheet, increasing borrowing needs. Moody’s Ratings analysis finds that early UK investment in adaptation would increase GDP resilience to significant climate shocks, although at the cost of higher public debt.
Using the IMF DIGNAD modelling tool calibrated to the UK, Moody’s found that in a 2040 flood shock, adaptation materially cushioned the economic impact of flooding, strengthening real GDP by around 0.3 percentage points under delayed action and 0.5 percentage points under a timely adaptation scenario.
At the same time, the model implies that adaptation leads to a higher debt trajectory, reflecting upfront investment costs. Debt to GDP rises by around 9-10 percentage points by 2045 in a timely adaptation scenario, compared to around 5-6 percentage points under delayed adaptation.
While stronger growth partly offsets these costs, the fiscal burden remains significant.
Methodology
The Moody’s RMS Europe Inland Flood HD Model™ — an advanced probabilistic risk management tool — was used to simulate losses from all sources of inland flooding across flood return periods (1 in 100 and 1 in 500 years).
To assess future flood risk, the analysis uses the Moody’s RMS Europe Inland Flood HD Climate Change Models with an RCP 4.5 intermediate-emissions scenario. This scenario is selected to reflect recent historical emissions trends and to account for the possibility of nonlinear climate responses. While climate is always evolving, the world is warming at a rate not seen in the past 10,000 years, according to the US National Aeronautics and Space Administration (NASA).
The modelled loss estimates are subject to uncertainty and should be interpreted as indicative rather than precise forecasts. Differences between estimated and realised losses may arise from variability in event characteristics, local flood mitigation measures, building attributes, claims behaviour, post event loss amplification and evolving insurance take up. Nevertheless, the use of consistent exposure definitions and a physically based modelling framework enables robust relative comparisons across geographies, event severities and emissions scenarios.