As natural catastrophes increase globally in both size and frequency, the question arises as to how both public and private entities can protect themselves from the resultant financial losses. Munich Re estimated that global natural catastrophes caused $270 billion in economic losses in 2022, but only $120 billion of these losses were insured. Swiss Re Institute revealed that around $280 billion in economic losses occurred in 2023. In 2024, the United States alone sustained $27 billion in losses caused by weather-related disasters. In an alarming sign of sensitivity to the growing risk, some insurers are withdrawing from states highly affected by natural disasters, including Florida and California. In this context, growing consideration is being given to using parametric insurance as a complement to traditional indemnity-based insurance contracts.
Most people’s understanding of insurance is based on the traditional insurance model. Under the traditional model, when physical damage occurs to an insured object, such as a vehicle, a claim is filed, an investigation occurs, and the insurer either denies or pays the claim. However, there is a niche form of insurance that is gaining popularity and applicability due to advances in technology as well as more reliable data measurements. This risk transfer model is parametric insurance, which is gaining credibility as a gap filler for losses that are typically left uninsured by traditional policies.
This article explores the basics of parametric insurance; its origins, history, and current and future applications; its challenges, drawbacks, and limitations; and two examples of how parametric policies can function as supplementary insurance.
The Basics of Parametric Insurance and Its Structural Elements
As its name suggests, parametric insurance coverage is triggered upon the occurrence of a specific event known as a “trigger event.” Once the trigger event meets a predefined parameter, a prearranged exact indemnity amount is paid. This type of risk transfer is composed of three design elements: (1) an objective measurable index quantifies the specific event; (2) the event meets or exceeds the index’s predefined threshold; and (3) the payout occurs according to the prearranged payout structure. In its definition of parametric insurance, Swiss Re expands on these conditions by defining a parametric product’s elements as (1) a pre-agreed settlement amount, (2) a predefined triggering event, (3) a predefined index that serves as the proxy for a financial loss, and (4) an insurable interest.
The predefined thresholds and payout structure, with minimal claim processing, creates an enticing package to supplement public and private entities’ risk management plans. Notably, the prearranged payout structure and ease of validating a trigger event result in indemnity payments within days. Swiss Re, Aon, Lockton, and Descartes Underwriting estimate that payments are processed within days or weeks of the trigger event. This contrasts with traditional insurance claims that can result in extensive investigations, and often litigation that may result in a full claim denial several years after a loss. But there are also downsides to parametric insurance as a risk management tool.
A discussion of the structure of parametric insurance can help clarify its benefits and challenges. Accordingly, the following sections address Swiss Re’s defined parametric elements to provide a broad overview of how each element applies in the procurement of a policy.
Pre-agreed settlement amount. Each parametric policy is individually written for the specific insured. This function provides inherent flexibility for purchasers. However, the pre-agreed payment does not need to be a high-risk gamble. This colloquial gamble refers to the occurrence of a trigger event that does not meet the required index and therefore precludes coverage for a loss. Instead, parametric insurance offers different forms of structured payouts. Some of these structures allow for payment in the event that a required index is not achieved. Other structures, for policyholders with increased risk appetite, provide a single payout if the predefined index level is met.
Strategic Risk Solutions (SRS) provides a brief overview of a payout structure that can be applied in the event of a triggering event: A theoretical parametric policy indemnifying hurricanes in Florida begins paying when a hurricane reaches Category 2 strength. In this model, the hurricane is the trigger event, and a Category 2 hurricane is the minimal index. Upon the occurrence of a Category 2 hurricane, a 25% payout is awarded. The payout amount continues to increase as the hurricane’s severity increases and ends with a 100% payout for a Category 5 hurricane.
The above example is commonly used to identify the flexibility, creativity, and individuality afforded by parametric insurance. The Financial Stability Institute (FSI) elaborates on and provides a detailed summary of several forms of payout structures. These structures include (1) a fixed payout (full payment upon an event reaching an single index threshold); (2) a proportional payment (payment proportional to the magnitude of the event); (3) an incremental payout (based on tiers of index values); and (4) a layered payout (multiple layers of coverage, each with its own trigger event and agreed-upon payout).
FSI also notes that there are hybrid forms of payout structures. These hybrid models provide comprehensive coverage for large-scale losses and require detailed loss verifications for rapid payouts. This payout model is designed for corporate and government solutions.
Triggering events. The second element is a predefined triggering event, which looks to the types of events that can be covered. In discussing triggering events, Swiss Re notes that an insurable triggering event must be fortuitous, capable of being independently and reliably monitored and reported, and able to be modeled. Additionally, an insured must maintain an insurable interest in the asset. Any potential risk that can provide highly reliable data and a credible index has the potential to be insured as a trigger event.
Currently, many of the parametric products are based on natural event triggers. Examples of natural events that qualify as trigger events include crop yields, precipitation, snowfall, soil moisture, temperature, wind generation, and solar irradiance. Industries that utilize parametric insurance are agriculture, construction, financial lenders, hospitality, manufacturing, renewable energy, and retail.
Because the trigger event must be related to the claimed loss, parametric policies must incorporate other model structures to ensure efficacy. The most popular method to do so is the “cat in a box” method. The “cat” is the natural catastrophe or the triggering event, and the “box” is the pre-agreed area where the risk lies. In order for coverage to trigger, the cat meeting the predefined index must occur within the box.
An alternative model is the “intensity model.” The intensity model provides coverage based on the reported intensity of the event that occurs at a particular insured location, rather than a broader geographic space. Swiss Re offers the STORM product, which utilizes the intensity model for tropical cyclones. STORM relies on the highest wind speed during the cyclone at the insured location and gets its independent report from Reask. New Paradigm Underwriting offers Shake and Pay, which relies on an intensity model that measures ground shaking during an earthquake. Shake and Pay receives its dataset for index measurements from the U.S. Geological Survey (USGS) ShakeMap.
In arguing in favor of intensity models, Swiss Re suggests that they allow a closer correlation between the loss location and a reduction in basis risk. Basis risk is an issue discussed more in depth below, but it is the result of an imperfect loss correlation. This imperfect correlation results in a policyholder receiving a lower than expected payout or no payout at all despite suffering financial losses from the triggering event.
Setting the index. At the core of parametric insurance is the index. An “index” is the required measurement threshold a triggering event must meet for coverage to apply. As discussed, a triggering event must be fortuitous, readily available for reporting and monitoring through a reliable independent third party, and modeled. A fortuitous loss simply means an unexpected, unforeseen event or accident. Fortuity is a cornerstone of the insurance industry as a whole, as insurance is effectively the transfer of risk of fortuitous losses from a policyholder to an insurer in return for payment of a premium.
Independent reliable reporting through third parties requires an examination of specific entities that concurrently record, monitor, and store data. Examples of independent agencies and respected datasets for indices include the Japanese Meteorological Agency, the USGS, the Australian Bureau of Meteorology, the National Hurricane Center, Moody’s HWind (wind speeds), and CoreLogic (hail sizes). The importance of the independence and reliability of the datasets cannot be overstated, because it is the data that provides the predefined index.
The use of independent third parties creates transparency and ensures that the trigger event meets the required index. In essence, utilization of independent data avoids bias and arguments over the cause of loss, which is rampant in the adjustment of claims submitted under traditional all-risk policies. The independent recording also allows for the modeling of the event. Further, the specific index can be tailored based on the third party’s historical data model to match a policyholder’s risk appetite.
Insurable interest. To qualify as insurance, parametric products must demonstrate that the insured possesses a legitimate insurable interest in the risk. An insured does so by demonstrating a financial interest in the asset and a financial loss if the triggering event occurs. A genuine risk transfer occurs when the trigger event is closely related to the insured’s financial loss. A qualifying example is the insured demonstrating an insurable interest in a building via a deed and proving risk transfer by reporting a claim, such as hail damage, after the insurer verifies that the hailstorm occurred at the pre-agreed index.
The Origin, Evolution, and Potential Future of Parametric Insurance
The concept of gap filler insurance dates back to the 1800s. Swiss Re identifies an early form of supplemental insurance that Hamburger Feuerkasse (Hamburg Fire Office) offered in 1817. It offered rental insurance as a supplement to fire insurance, and thus the insured would receive an early form of business income insurance in addition to typical insurance for property damage caused by a fire. Despite this humble beginning, the idea of what we know as parametric insurance products lay dormant. As the world began to experience high-level natural disasters that traditional insurance alone could not compensate for, an alternative model developed.
The origin of modern parametric insurance occurred in the late 1990s as an index-based solution for farmers in developing Asian countries. The index-based solution was to mitigate the financial impact and losses farmers sustained due to severe weather. Although index based, parametric insurance is distinguishable from index insurance. Parametric policies require a specific threshold event. In contrast, index insurance policies review specific indexes over a temporal period, such as crop yields over an entire grow cycle, or longer.
Catastrophe bonds (cat bonds) are a rung of the parametric insurance evolutionary ladder. Cat bonds gained prominence as a form of reinsurance due to the fact that the bonds transferred high magnitude catastrophes from insurers to investors. Upon a significant natural disaster, many cat bonds would pay insurers directly based on parametric triggers. In fact, an early parametric insurance policy was actually a cat bond issued in 1999 to protect Disneyland Tokyo from earthquakes.
In the early 2000s, Swiss Re, AXA, and Munich Re began offering parametric products. A notable development occurred in 2007 with the establishment of the Caribbean Catastrophe Risk Insurance Facility (CCRIF). The CCRIF launched the first multi-country risk pool that adopted parametric insurance to provide rapid, short-term liquidity in the event of a natural disaster.
Additional technological advancements and increased data availability allowed insurers to launch the first mass-market parametric insurance policies. In 2011, Swiss Re began to offer parametric policies in Japan for tsunamis, with the index based on wave height. In 2017, Swiss Re introduced another form of parametric insurance called Insur8. Insur8 is a typhoon warning policy that is designed to mitigate business interruptions when a typhoon warning of eight or higher is issued. In response to significant losses incurred by French vineyards in 2017, Meteo Protect offered parametric insurance based on an index of temperatures during the growing season.
Significantly, Marsh, in partnership with Metabiota and Munich Re, offered a parametric product for pandemics called PathogenRX in 2018, but not a single policy was sold. PathogenRX was designed to protect retailers, wholesalers, restaurants, and food and beverage manufacturers from financial losses stemming from an epidemic or pandemic. As many know, commercial insureds learned that traditional all-risk commercial policies did not provide business interruption coverage for pandemics. In this instance, PathogenRX would have covered the affected businesses during the COVID-19 pandemic.
The current generation of parametric products is linked to natural catastrophes due to the reliable datasets. Current users of parametric insurance include real estate developers, investors, and owners; hotels, resorts, and other tourism-related businesses, including airports; and solar, wind, and hydroelectric farms. Parametric insurance is also being used as the first layer of protection for homeowners in high-risk areas. Examples of these initial layer products include StormPeace offered by FedNat Insurance Company in Florida, which pays out within 72 hours of a hurricane. Jumpstart offers prompt payouts for earthquakes in California based on an intensity structure.
Aside from direct damage or economic losses caused by catastrophic weather events, parametric offerings can address other risks. But it must be reiterated that each risk must be connected to a reliable index. For instance, Gallagher identifies expansion into energy utilities based on wind yields, solar radiation, water levels, and flow rates as indices for the respective utility. Gallagher points to construction delays as a potential risk based on weather conditions, as well as supply chain holdups based on external factors including fires or floods. Significantly, business interruption coverage is another key risk that can be supplemented by parametric insurance. Descartes advertises parametric insurance as a method to insure nonphysical contingent economic losses, such as financial losses incurred from decreased tourism.
As parametric product offerings expand, so does their potential value. For instance, the global parametric industry market was valued at approximately $11.7 billion in 2021. By 2031, it is estimated that this value could rise to $29.3 billion. The largest parametric insurers include AXA, AIG, Allianz, Aon, Berkshire Hathaway Specialty Insurance, Chubb, and Lloyd’s of London, which together make up a combined 51% market share. Swiss Re, Munich Re, and Marsh & McLennan are also major insurers in the parametric product market.
Domestically, the U.S. parametric insurance market was valued at $4.29 billion in 2024. It is anticipated that this amount will only increase as the public and private sectors look to supplement their respective risk management plans.
Recent technological innovations have increased the efficiency and reliability of parametric products, which further advances the products’ appeal. Blockchain technology allows insurers to record contracts and claims on decentralized ledgers. The use of “smart contracts” reliant on blockchains enables insurers to create programs that automatically pull data from the independent reporter and insert the data into the contract to create an automatic payment. As smart contracts can be coded to run when predetermined conditions are met, the technology can be used to make parametric insurance more efficient. Machine learning is also used to refine risk models and prediction algorithms by processing historical data, real-time data, risk patterns, and forecasts. This leads to dynamic pricing and models that enable insurers to efficiently assess proper premiums and coverage.
Indeed, more insurers are beginning to look to parameter-based policies to address complicated and/or highly specific risks to offer increased risk transfer opportunities.
The Challenges and Benefits of Parametric Insurance
Challenges. The most significant drawback to parametric insurance is that the coverage may not fully indemnify a policyholder for actual sustained losses. This situation occurs due to a basis risk, which was addressed briefly above. To reiterate, basis risk occurs when the index does not effectively correlate with the actual loss and leads to a gap in coverage. This may result in an insured being left wholly uncompensated or severely undercompensated for marginally avoiding an index. A basis risk can arise from inadequate datasets, misaligned geographic areas used in a cat in the box model, inaccurate models, misalignment of the risk insured and financial resiliency of the policyholder, and the use of temporal activity data that does not align with the period of loss.
The basis risk issue is amplified by parametric insurance, where significant losses can be incurred. An example is when a $150 million cat bond went unpaid due to the index’s required minimum air pressure level having been narrowly missed. In another instance, a 2018 volcanic eruption in Bali went uninsured by a parametric policy procured to protect the nation’s tourism industry. The Bali parametric policy looked to the distance of the businesses from the volcano and the level of ashfall. The required indexes were unmet and caused a wholly uninsured loss. These examples demonstrate the significant cost of losses that can be incurred based on the failure to meet an index. As such, it is tantamount that a correct index is selected, and a basis risk is avoided or minimized.
Regulatory issues also arise in the U.S. since parametric insurance is nearly unregulated. The traditional insurance model provides states’ statutory framework, and thus the basis for case authority. This creates an issue as to how courts may interpret parametric policies without legislative guidance on the subject and leaves courts applying traditional insurance concepts to a nontraditional model.
New York recently authorized the sale and purchase of parametric policies within the state. Pursuant to New York Insurance Law section 1113, parametric insurance is defined as insurance against the occurrence of a weather-related event. Tennessee amended its insurance code in 2021 to define parametric insurance as a “type of insurance that does not indemnify pure loss, but ex ante agrees to make a payment upon the occurrence of a triggering event.” Vermont also recently passed legislation that allows captive insurance companies to enter into parametric insurance contracts. Connecticut’s legislature is considering a bill that would conduct a feasibility study to provide parametric insurance for farmers affected by severe weather. California is reviewing the potential benefits of parametric insurance in light of the progressively worsening natural disasters within the state. Absent express statutory and regulatory guidelines, parametric insurance falls under the ambit of the respective state’s statutory framework applicable to traditional insurance. The lack of express legislation will likely change as states modify their respective insurance codes.
Another material drawback is the lack of education and awareness about the product. While several highly involved global brokerages are aware of parametric insurance, local consumer-facing brokers possess minimal product awareness. The proper education of brokers regarding the limits and conditionality of parametric insurance is critical. This is because brokers are the educators of the consumer. Insureds rely on their broker’s knowledge to procure the correct type of insurance. A lack of awareness and education may lead to insureds receiving inadequate parametric policies or being exposed to losses that could otherwise be covered by a parametric policy properly paired with traditional insurance.
A notable challenge is the cost of capacity. Capacity is the maximum amount of risk a company can assume based on its financial resources. Insurers already underwrite catastrophe coverage via first-party property damage polices, and the addition of parametric products only expands insurers’ risk assumption for catastrophic losses. Moreover, parametric policies pay claims in a more reliable manner. In contrast, traditional policies contain conditions, limitations, and exclusions that preclude coverage even for potentially covered events. Thus, many insurers must gauge their cost of capacity when underwriting parametric policies in highly susceptible loss areas. A single large event could overwhelm an insurer’s capacity.
Parametric insurance is also limited to predefined exposures that are in fact insurable under the discussed elements. Parametric insurance cannot be used to underwrite uninsurable risks like performance-related exposures. For example, the inability to complete a construction project caused by hazardous material contamination is unacceptable, since the risk was manageable due to soil testing and there is no natural trigger event. There are certain risks that insurers will not and cannot underwrite through parametric insurance. That is why the policies must be paired with traditional insurance.
Benefits. Nonetheless, parametric insurance undoubtedly provides almost immediate payouts when a trigger event meets the required index. Swiss Re estimates that, depending on the risk insured, payouts for cyclones can occur between two and five days, earthquake payouts occur within 10 days, and hail damages are paid within two to seven days. As noted, other insurers such as Aon and Descartes estimate payments within days or weeks after a verified trigger event. Thus, the speed of payouts is a substantial benefit. This is particularly so when parametric insurance acts as a first layer of coverage to a traditional policy.
Specific, individually tailored policies are another undeniable benefit. Policyholders work directly with insurers to ensure the exact risks and locations to be insured. The ability to identify distinct trigger events and indices provides policyholders with a plethora of options to craft a bespoke policy, as does the ability to set the policy limits, whether they be single payout, proportional, incremental, or hybrid in nature. The contrast between the cat in the box and intensity model structures promotes an additional individual experience — an experience that corporations, governments, and even homeowners can appreciate.
The prearranged payout structure, trigger event, and index also provide consumers with predictability. Since the policyholder should directly engage in the crafting of a parametric policy, they then know what to expect in the event of a loss. This predictability creates confidence in the product.
A final benefit is essential to the reasoning behind parametric insurance: it is a gap filler. Swiss Re notes that parametric insurance is to be used as a complement to fill coverage gaps left by traditional indemnity policies. Allianz’s Risk Barometer 2025 survey lists business interruption as the second most important business risk. Notably, 72% of supply chain companies identified the COVID-19 pandemic’s negative impact on their industry. Businesses directly suffered from this supply chain disruption, and in some instances government-mandated closures, as a result of the pandemic. A parametric policy, such as Marsh’s PathogenRX, could have alleviated losses caused by COVID-19 by providing coverage for business interruption.
Parametric Insurance as a Gap Filler
The following examples illustrate how parametric policies can supplement traditional policies in regard to a small-scale business. The theoretical policyholder is a small local chain supermarket in South Buffalo, New York. The policyholder operates three markets within a 40-mile radius, with each market located in a separate town. This policyholder survived the COVID-19 pandemic and well-known Buffalo blizzards. As the insured seeks to expand its business, it structures its current risk management plan to address the inclement weather and supply chain disruptions it recently experienced. To do so, the policyholder discusses its concerns with its broker, who is educated and knowledgeable in parametric insurance. After some discussion, the policyholder elects to procure two parametric policies.
The first parametric policy’s prearranged payout structure is a fixed payout upon a single trigger event with an applicable limit of $500,000. Since it is Buffalo, the triggering event is a blizzard, and the policy is based on a cat in the box structure that covers the 40-mile radius where the policyholder’s markets are located. The policy’s index is set as a single snowfall event of 15 feet.
The second parametric policy’s prearranged payout structure is a proportional payment. As the policyholder routinely imports its produce from South America, its triggering event is an earthquake and relies on an intensity scale. The area selected is the Panama Canal, which is the port that transports most of the imported produce. The index is established at a 100% shake intensity based on prior history in the area verified by the USGS. The policyholder provides evidence of an insurable interest through a sale contract that demonstrates the insured’s financial interest in the produce and its storage location at the port. This policy’s limit is $1 million.
Cat in the box weather event. The first scenario analyzes the effect of the policyholder’s blizzard policy. During the winter, South Buffalo suffers a catastrophic weather event. A blizzard occurs over the course of a day and deposits 17 feet of snow. The event occurs within the entire 40-mile radius of the policyholder’s markets, and each market is listed on the parametric policy as an insured risk. In addition to snowfall, temperatures drop to below freezing and cause pipe ruptures at two of the markets. However, the insured can still operate its business despite the plumbing damage. The insured sustains a total $400,000 loss. Unfortunately, the policyholder’s traditional all-risk policy contains an applicable exclusion, and coverage is denied for the loss in its entirety.
This is where the insured’s updated risk management plan takes effect. As the trigger event and the index’s required magnitude occurred within the policyholder’s box, the policy’s parameters are met. The insurable interest is verified by the insured’s notice of claim of blizzard-caused damage and the blizzard’s independent verification through the National Weather Service. As each parametric element has been met, the policyholder is completely indemnified by the single $500,000 payout limit. In this scenario, the insured’s parametric policy filled the gap left by its traditional insurance policy.
Intensity-based earthquake. The second scenario examines how the insured can protect against a supply chain disruption to replace a business income loss. As COVID-19 showed the policyholder, disruptions in supply chains and government-mandated business closures are not covered by all-risk policies. This is because a covered cause of loss that results in direct physical loss of or damage to insured property is a requirement for business income coverage. Based on its loss experience, the policyholder identified the Panama Canal as a point of interest because it contains the main port through which its imported produce travels. The policyholder is also aware of Panama’s susceptibility to earthquakes since it is located on the Pedro Miguel Fault.
A 7.0 magnitude earthquake occurs in the direct vicinity of the Panama Canal. The shake intensity measured at the specific port insured by the policy is measured at 75% based on the verified data collected by the USGS. The earthquake resulted in a large disruption to the policyholder’s produce importation and an estimated $700,000 loss. This is due to the inability to receive significant amounts of produce for several weeks. However, since the intensity rating at the insured port is 75%, the insured does not receive the entire policy limit. Instead, the proportional payout structure permits recovery of $750,000, which is still enough to cover the business income losses sustained by the policyholder. The policyholder then submits evidence of its insurable interest through the sale contract.
Although the policyholder did not receive the policy limit, it was still wholly indemnified for the loss. If the policyholder were solely reliant on its traditional commercial insurance policy, it would have received no recovery due to the lack of any physical damage to its markets in Buffalo. This scenario demonstrates how businesses can identify historic weather events at specific locations to insure themselves from supply chain disruptions. The theoretical market insuring its import interest at a specific port is just one example.
Several other industries can rely on this method to protect themselves from insurance gaps. For instance, California wineries can procure parametric policies for supplying vineyards. The winery can demonstrate an insurable interest through a sales contract of the grapes and then insure the vineyard contractually obligated to produce the grapes. Auto dealerships can pinpoint the exact points of exit and entry through which their automobiles travel. Technology firms can look to the areas from which they receive semiconductors. Simply put, parametric insurance’s flexibility and individually tailored structure allow for broad protection.
Conclusion
Parametric insurance provides an intriguing solution for gaps in insurance coverage. Although it faces its own challenges, specifically basis risk, parametric products offer highly tailored policies with prompt payouts in the event of catastrophic losses. Moreover, its characteristic ability to apply to a broad range of events with measurable indices creates an appetizing complement to traditional insurance — a complement that will only grow as public and private sectors look to address ever-worsening natural catastrophes that cause both physical damage and economic losses.
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