The insurance protection gap is the difference between total economic losses from insurable events and the share of those losses that is covered by insurance. Moody’s focuses on the protection gap related to natural catastrophes, which is felt most acutely because such events inflict substantial losses at a single point in time. Estimates of the protection gap vary, but uninsured losses frequently exceed insured ones by a wide margin. For example, Moody’s estimates that less than 20% of average annual losses from earthquakes in the US are covered by insurance, with coverage levels even lower (less than 15%) in the very seismically-exposed state of California.
One obstacle to accurately measuring the protection gap is that the definition of total economic loss varies widely. Some estimates take account solely of direct catastrophe impacts, principally physical damages and business interruption. While these can be assessed accurately, they do not capture the full force of most catastrophe events.
Other estimates also include indirect losses such as emergency response costs, reductions in tax revenue, supply chain effects, migration, and health costs. These estimates better reflect the impact of catastrophes, but since many of their components are hard to measure, they are also less precise. Using this broader definition, Moody’s estimates that the global economic impact of physical risks alone could add as much as $41.4 trillion to a baseline without physical risks in 2050. Only a fraction of this is likely to be insured.
The protection gap varies widely
Uninsured losses often go largely unreported because they are not compiled centrally. As a result, they receive little attention, even though they are a significant drain on the resources of the governments, households, banks and businesses that absorb them. This makes the insurance protection gap a systemic social and economic problem.
The protection gap is typically not the result of insurer failure or unwillingness to pay claims. Instead, it primarily reflects:
- Low or no take-up of insurance. This can arise in low income countries where insurance markets remain underdeveloped, and elsewhere because coverage for specific risks is unavailable or unaffordable. Low risk awareness and a widespread expectation that governments will cover losses can also hold back insurance coverage.
- Insurance coverage limitations arising from exclusions, deductibles, sub limits, and mismatches between policy terms and loss drivers.
- Indirect losses such as emergency response costs, supply chain impacts or reductions in tax revenue, which are often not easily insurable.
These factors apply to varying degrees across regions and for each type of insured risk, depending on local laws, historical disaster experience and insurance availability and affordability. The size of the protection gap therefore varies widely by region and by risk.
In general, the protection gap is wider in developing economies, where take-up of insurance tends to be low because it is either unavailable or prohibitively expensive. For example, less than 5% of the more than $4 billion loss caused by Cyclone Ditwah in Sri Lanka in 2025 was insured.
Conversely, the gap is lower as a share of total losses in advanced economies, where insurance is more widely available and a higher proportion of households and businesses can afford it. In Germany, this limits average annual uninsured storm-related losses to around 15% of the corresponding direct economic loss.
High levels of uninsured risk are nonetheless common even in highly developed countries. The protection gap associated with the 2014 earthquake in South Napa, California was estimated at greater than 90% of the total economic loss. This reflected both low take up of earthquake insurance and relatively high deductibles where protection was in place.
Similarly, there are pockets of high insurance coverage, and hence, low protection gaps, in less advanced economies. When Hurricane Melissa made landfall in Jamaica in 2025, high levels of insurance coverage among the island’s hotels and larger businesses capped the overall uninsured loss rate at 67%. This compares with close to 100% for homeowners in the worst affected parishes.
The protection gap can change quickly within a single region after a major disaster. This is because large events typically raise risk awareness and encourage take-up of insurance. Demand for flood insurance has been increasing steadily in Germany because of repeated flood events since the start of the century, including the severe Bernd floods of 2021.
Major disasters often also encourage the authorities to put in place effective defenses as part of the reconstruction process, which reduces future losses. Upgrades in flood defenses have led to a dramatic improvement in regional flood protection standards in the New Orleans area following Hurricane Katrina in 2005.
However, a rapid succession of severe catastrophes in the same area can have the opposite effect, as frequent losses raise insurance costs and reduce insurers’ willingness to offer cover. This contributed to declining insurance availability in parts of California after the 2017 Tubbs fire and subsequent wildfires.
Understanding the changeable nature of the protection gap across risks, regions and time allows for more targeted and effective management measures.
Emerging market gaps are wider, but exceptions exist
Six recent catastrophes, one uncomfortable pattern: The amount paid by insurers is dwarfed by what wasn’t covered. Advanced economies or not, the uninsured slice — the protection gap — is where the real bill lands.
At a global level, economic losses from natural catastrophes have increased materially over recent decades. This is driven in part by increases in the frequency and severity of extreme weather, a trend that is likely to continue. For example, based on a US model, Moody’s estimates that average annual damages from acute physical climate perils may increase by as much as 26% by 2050.
This change in extreme weather is compounded by population growth in exposed areas. A 2024 Moody’s study shows that between 1975 and 2020, the global population living in flood-prone regions increased significantly more quickly than the total population. As a result, approximately 2.7 billion individuals — roughly one in three people globally — lived in areas at risk of flooding as of 2020. This proportion is likely to rise even further.
Uneven economic growth is another factor. Emerging markets are growing faster than the global average, a trend which Moody’s expects to continue in 2026. However, low insurance penetration in these countries means that a large share of the assets generated by economic expansion remains uninsured. Insured losses are rising more slowly than economic losses as a result.
Rich world cover, emerging-world exposure
The protection gap is also getting larger because insurance coverage has stagnated or retreated for some risks and in some regions. This reflects rising insurance prices in response to an increase in the frequency and severity of certain events, which puts insurance beyond the means of some households and businesses. The industry has also responded with higher deductibles and lower coverage limits, which pushes up uninsured exposure even where insurance is in place.
Higher costs and restrictions have contributed to a decline in insurance take-up rates in California’s highest-risk wildfire zones, for example. As private carriers pull back, homeowners are increasingly turning to the Fair Access to Insurance Requirements (FAIR) Plan, California’s insurer of last resort. FAIR has historically set coverage limits that may not fully cover the reconstruction costs of properties in affluent, high-risk areas.
Changes in the regional distribution of catastrophe events have also helped widen the protection gap. Extreme weather is expanding into regions that have historically had little exposure to it, and where preparedness, including appropriate insurance coverage, is correspondingly low. In addition, emerging chronic physical climate risks, such as water stress and heatwaves, are causing increasingly large and frequent economic losses but remain largely uncovered by insurance. Around 95% of losses related to the European heatwave of 2025 were uninsured.
As a result of these trends, economic losses from natural catastrophes are growing faster than insured losses, even in years when there are no outsized events.
Protection gap risk falls mainly on governments
Uninsured losses do not disappear. Instead, they are absorbed by governments, households, banks, and businesses. Governments bear the lion’s share of the cost in the form of post event disaster assistance, infrastructure repair and economic support. The Chilean government, for example, covered almost half the economic losses caused by the 2010 Maule earthquake. In emerging markets, unforeseen expenditure of this kind absorbs funds intended for schools, roads and clinics, holding back economic development.
Uninsured losses can be seen as a contingent liability on the public balance sheet which is rarely quantified before major loss events, but which materializes abruptly after them. Governments absorb direct costs related to disaster relief and reconstruction. Lower tax revenues because of economic disruption and consequently higher borrowing put additional strain on the public balance sheet.
These pressures can be particularly acute for smaller economies and local governments, with implications for fiscal sustainability and credit quality. Over time, repeated events can raise baseline spending, reduce fiscal flexibility and, in more exposed countries, contribute to higher risk premia and borrowing costs.
For example, increased flood risk is a growing credit challenge for local economies and tax bases in the eastern and southern US, exacerbated by low insurance coverage. Coastal and inland floods are becoming more frequent and severe in the region, leading to substantial property damage and economic disruption. A high and growing percentage of residential and commercial properties in high risk areas do not carry flood insurance, while federal disaster aid typically covers only a fraction of the costs of immediate clean up and repair efforts. This has increased property insurance costs and reduced property values, and has highlighted the need for extensive investment in physical climate adaptation infrastructure.
Risk reduction and transfer is key
Large protection gaps create long-term structural challenges as well as immediate post-event fiscal pressures. This is because:
- They lead to reliance on post disaster public support, which weakens incentives for risk mitigation and insurance uptake.
- Uninsured losses tend to fall disproportionately on lower income households, exacerbating inequality and slowing recovery.
- Slow economic recovery can trigger an exodus of households and businesses from affected areas, as seen in areas around New Orleans in the aftermath of Hurricane Katrina in 2005.
Governments, therefore, have a strong incentive to close or narrow the protection gap. They have an important role in designing and funding risk reduction measures, such as flood defenses and wind resistant building standards. They can also create risk transfer mechanisms, such as publicly funded programs to improve the availability and affordability of insurance.
The UK provides a good example of public policy helping to support insurance coverage. Flood Re, a public-private reinsurance provider, improves insurance affordability for households in areas where flood risk is high. This supports residential coverage, which helps limit immediate fiscal pressure on the UK public sector.
The UK’s country-wide flood insurance protection gap across all property is as a result relatively narrow at around 10% of total economic losses. However, rising physical climate risk – including increasing exposure in flood-prone areas — tighter reinsurance conditions and Flood Re’s scheduled closure in 2039 could widen protection gaps over time, shifting more losses onto the public sector.
Businesses and households can also take steps to manage the risks they face, rather than relying on insurance coverage and/or government support alone. Capital market investors can also contribute through risk-transfer mechanisms such as catastrophe bonds. This opens the door to new collaboration between central and local governments, capital markets, and the private sector.
A key obstacle for governments, businesses, and households wishing to better manage their uninsured loss exposure is that there is little visibility over its potential scale. Insured losses are rapidly reported and analyzed in the aftermath of an event, but measurement of uninsured losses is fragmented, delayed, and incomplete. Data may be dispersed across government agencies, aid programs, and household surveys, making aggregation difficult. Variable definitions and reporting standards of economic losses are a further impediment.
Compiling a comprehensive overview of economic losses is possible, as demonstrated by the meticulous data gathering exercise that followed the 2010 earthquake that struck off the coast of the Maule Region of central Chile. However, this requires a conscious, coordinated effort which is often deprioritized in the immediate aftermath of a catastrophe event.
The Maule earthquake: Catastrophe costs laid bare
A massive Mw8.8 earthquake struck the Maule Region, around 300km south of Santiago, Chile on Feb. 27, 2010, damaging an estimated 370,000 homes — roughly 9% of the country’s building stock. The earthquake is the rare disaster where every dollar of the $23.4 billion loss was able to be traced by a one-off, OECD-funded effort — proof that the protection gap can be made visible. Toggle between views to see the gap a couple of ways:
Only about 24% of homes were insured (and barely half that in hard-hit Concepción), so insurers paid 125,000 residential claims worth $2.78 billion, while the government funded repair and rebuild subsidies for lower-income owners and some $4.8 billion of repairs to schools, hospitals and infrastructure.
Country-wide output fell 5% in the month after the quake, and taxes on the mining sector were raised to help plug the gap. Crucially, an OECD-funded effort led by Robert Muir-Wood, currently Chief Research Officer at Moody’s, traced exactly who paid — insurers, government, households and business — within months of the event, showing how a concentrated, coordinated push can make the protection gap visible where it usually stays hidden.
Poor visibility over the protection gap means that households, businesses, and governments frequently underestimate the true economic cost of disasters, and the size of the contingent liabilities that their respective balance sheets must absorb.
This has tangible consequences:
- Risk is underpriced in both public and private decision making.
- Investment in mitigation and adaptation is deprioritized relative to post event response.
- Long-term fiscal and credit risks remain opaque until after losses occur.
In effect, what cannot be seen cannot be managed.
Insurers use risk models to estimate claims from catastrophe events. These models use insurance coverage data, information on the physical characteristics of the affected area, historical impact data, and a scientific understanding of catastrophe behavior to calculate the expected impact of a wide range of real or hypothetical disasters.
The same models can be leveraged beyond the insurance industry. Businesses can use them to assess potential impacts on their operations, and investors can use them to uncover potential threats to their portfolios. Banks are starting to use catastrophe models alongside loan data and credit risk analytics to quantify the effect of large catastrophe events on their loan books, including mortgage collateral devaluation. They could similarly be used in conjunction with economic data to better understand the economic and fiscal consequences of major catastrophe events.
The common purpose of all these applications is to make risks visible. Extending catastrophe models beyond their ‘traditional’ use case in the insurance industry can significantly improve visibility of uninsured losses. Crucially, they can provide such visibility from the bottom up, down to the level of individual assets, and can also capture how insured and uninsured losses vary across regions, time and different risk categories.
Once visible and quantified, uninsured losses would become more manageable:
- Governments would be better able to quantify fiscal exposure to catastrophe events and move from reactive post-event spending to more proactive and cost-effective investment in prevention and mitigation.
- Investors would gain a better understanding of the economic and financial impact of extreme events. Banks and asset managers would gain insights into uninsured financial risks and could complement their insurance protection with targeted risk management measures.
- Similarly, insurers and reinsurers’ ability to evaluate coverage gaps would improve, helping them design targeted solutions. Banks and asset managers would at the same time gain insights into the uninsured financial risks they are exposed to. This could encourage them to complement their insurance protection with targeted risk management measures.
- Investors, businesses and households would be better equipped to identify and manage their uninsured risk exposure and put in place targeted risk management measures. In combination, these changes would reduce reliance on government support and allow for more rapid post-event recovery.
Using granular insights from catastrophe models to shed light on uninsured losses can therefore become a catalyst for more effective preventative measures. This approach could also improve decision makers’ shared understanding of risk as they seek ways to narrow the global protection gap.
s a widening, systemic risk. Here is why it matters, who absorbs the cost, and how catastrophe models can help bring it into view.