Captive insurance is the most popular form of alternative risk financing1 due to the myriad of benefits, both economic and noneconomic, that it can achieve. Among these benefits is the ability of the captive insurance company to write policies that typically aren’t available in the commercial market. Many companies are faced with unique or hard-to-place risks that a standard indemnity policy may not cover. Some of these unique risks can more easily be addressed through existing policy forms. For example, in the post-COVID-19 world, some captives are incorporating pandemic business interruption risk into their captives2 However, for other more unusual risks, there is no clear-cut solution. Trying to draft a policy for these unusual risks, along with getting regulatory approval, can be difficult. These risks may be novel to both auditors and captive regulators, who may be wary to approve a policy that has no obvious history of risk transfer. However, there may be one underutilized solution to insure these gaps in coverage—parametric policies.
What is a parametric policy?
According to the National Association of Insurance Commissioners (NAIC),3 parametric insurance (sometimes also referred to as “index-based” insurance) is defined as a “type of insurance contract that insures a policyholder against the occurrence of a specific event by paying a set amount based on the magnitude of the event, as opposed to the magnitude of the losses in a traditional indemnity policy.” What does this mean exactly? In a traditional indemnity policy, the loss amounts eventually paid to the claimant following the occurrence of a claim are usually not known with certainty. There is typically a claim adjustment process that often includes litigation that could delay the final settlement of a claim for several years. With a parametric policy, the loss payout is predetermined prior to the issuance of the policy. There are then certain measurable metrics, called the “trigger(s),” that need to be met for the payment to be made. Once all conditions of the trigger have been met, the parametric policy pays out the predetermined loss amount to the policyholder. There are two necessary criteria for determining the trigger: 1) it must be independently and objectively measurable, and 2) it must be able to be modeled.4 Some parametric policies may have more than one trigger that must be met before payout occurs, or may have several triggers depending on the situation, such as a gradation in payout based on the intensity of a storm.
These parametric policies can often be more easily explained through a noninsurance example—sports betting. Take horse racing, for example. At the racetrack, you can buy a ticket with a bet that a certain horse will win the race. The amount you spent to purchase this ticket would be analogous to the premium paid in a parametric policy. The ticket will display the amount the purchaser will win if the selected horse wins the race. This payout is predetermined prior to the race and is typically based on odds, or probabilities, just like an insurance contract. The trigger in this example would be simple—if the selected horse wins the race, the trigger is met and a payout occurs; otherwise, there is no payout. The only difference between this simple example and a parametric policy is that, with a parametric policy, the predetermined payment is related to reimbursing a loss.
Insurance examples of parametric policies
How can a captive use a parametric policy to help complement its traditional indemnity policies and bridge any gaps in coverage? Historically, parametric policies have been primarily used in the property catastrophe market. A popular example of a trigger is a specified measure of wind speed in a hurricane that when modeled causes a certain loss (i.e., the estimated loss at that wind speed would be the payout). If, and when, a hurricane occurs, and the specified wind speed is attained, then the parametric policy would immediately pay out the losses to the policyholder, helping to quickly improve cash flow in the wake of the hurricane. Another popular trigger in the property catastrophe market is the magnitude of an earthquake. Once the specified magnitude is reached, the policy would pay out. Because many of the triggers in the property catastrophe market are objective and determinable, it is easy to see why parametric triggers are popular. Furthermore, the immediate payout helps eliminate any concerns about post-loss cash flow.
Continuing with the property catastrophe market, another popular form of parametric contract is the industry loss warranty (ILW). An ILW is a type of index-based policy in which the trigger is based on the total industry insured loss experience for a particular event.5 The trigger is typically a specified dollar amount that the industry (rather than the policyholder) must incur from a particular event in order to pay out. Oftentimes an ILW with an industry loss trigger will be coupled with a policyholder-specific trigger specifying a loss that the policyholder must also incur to generate a payout. So, for these dual-trigger contracts, both the industry losses and the policyholder-specific losses must reach their specified thresholds in order for the policyholder to receive a payout.
While parametric policies are most often used in the property catastrophe market, they are not limited as such. Parametric policies can cover any type of objectively measurable event that causes a loss and can be modeled. For example, construction companies could define a trigger such as a number of days with precipitation. Rain and snow can delay projects and can lead to lost income on other projects that were not undertaken due to the delay. A captive whose parent is in the construction industry can use historical company data, along with economic data and weather data, to model and determine the appropriate payout and trigger for this type of parametric policy.
For many in the retail industry, the COVID-19 pandemic brought about store closings and lost sales. Rather than the company purchasing pandemic business interruption coverage through a traditional indemnity policy, the retail captive could write a parametric policy where the trigger is a predetermined decrease in sales due to a pandemic. While many retail businesses were forced to close due to government restrictions, the parametric policy would be able to provide cash flow to help the company stay afloat and pay its employees.
For the healthcare industry, a wide variety of triggers could be utilized. For example, a certain percentage decrease in market share for a medical device or pharmaceutical manufacturer could be a trigger, and the payout could be determined based on the lost income due to this decrease in market share. This type of trigger can also apply to many of the other popular industries that use captives, such as the manufacturing, energy, and technology industries.6
Figure 1: Examples of triggers
Overall, parametric policies can incorporate unique coverage in a way that traditional indemnity policies cannot. They can function as a funding tool in all areas of potential loss, and can provide an immediate influx of cash following the activation of the trigger.
Now that we have a better understanding of parametric policies and have gone through a few examples, let’s take a deep dive into the fundamental differences of them from the traditional indemnity policies that your captive may write.
Comparing to a traditional indemnity policy
Both parametric and traditional indemnity insurance policies exist for the purpose of reimbursing a loss event. However, the manners in which the policies reimburse these losses are fundamentally different. We’ve previously dissected the parametric trigger and gone through a few examples. But what is a trigger for a traditional indemnity policy? The trigger may not be as transparent, but it is relatively simple and something with which all captives are familiar—the occurrence of a claim!
When a claim occurs for a traditional indemnity policy, the trigger is met, and the claimant is able to recoup the actual loss amounts (subject to policy terms). As mentioned above, in a parametric policy, once the specified trigger(s) have been met, then the policy pays the predetermined amount, which may or may not reimburse the full loss amount. This brings up one of the key downsides to parametric policies—basis risk. Basis risk is the risk that the payout from the policy is not perfectly correlated with an insured’s actual losses (i.e., the payout from the policy does not fully reimburse the actual losses sustained from an event).7 In the event that the payout from a parametric policy is less than the actual loss amounts, the results can be devastating, particularly in the wake of a catastrophe. The captive would need to utilize its capital and surplus in order to pay out claims, which may or may not be sufficient. An example of this would be the instance where the captive purchases an ILW with an industry trigger. If the captive experiences significant losses, but the industry trigger is not met, then the captive may have insufficient funds to pay the policyholder.
However, in some instances, basis risk can also be beneficial for the captive. In the same ILW example, were industry losses to exceed the threshold but the captive sustained minimal losses, then the captive would over-recover on the policy. This recovery would help to build additional surplus (or provide a dividend to the parent). The existence of basis risk is where the dual trigger contract, with both an industry trigger and an insurer-specific trigger, may be useful. The insurer-specific trigger helps mitigate basis risk, whereas the industry trigger protects against moral hazard (the event in which the insurer may overstate losses to receive a payout).
While basis risk is a potential drawback to parametric policies, parametric insurance also has benefits. Arguably, one of the most important benefits that parametric policies have over indemnity policies is that they completely remove the claim adjustment process. Claim adjustment costs can be expensive, particularly for longer-tailed lines of business. The administrative costs of keeping claims open for years and years can add up. With a parametric policy’s immediate payout, a captive can evade this process and can also improve cash flow in the event of a loss. Policy terms are another benefit of parametric insurance, as they can be written on a multiyear basis,8 allowing the parent the ability to tailor coverage uniquely for the risks of the captive.
Figure 2: Parametric vs. indemnity policies
|Parametric Policy||Indemnity Policy|
|Trigger||Specified Threshold Attained||Occurrence of a Claim|
|Payment||Predetermined Amount||Recovery of Actual Losses Incurred|
|Basis Risk||Need to Correlate Index With Losses||Minimal|
|Moral Hazard||Minimized With a Dual Trigger/Modeling||Minimized With Deductibles/Exclusions|
|Claim Adjustment Process||Quick Payout||Can Be Long, Expensive Process|
|Policy Term||Multiyear||Single Year|
Now that we’ve provided the benefits of incorporating a parametric policy into your captive, how does your captive go about pricing this policy? That is where the actuary comes in.
The role of the actuary
For pricing traditional indemnity policies written by your captive, your actuary most likely relies on historical claim and exposure data. The actuary would typically build historical data triangles, estimate losses using commonly accepted actuarial techniques, and project losses for the upcoming year.
However, for parametric policies, standard actuarial techniques might not be sufficient. As parametric policies are meant to bridge gaps in your captive’s insurance program, the events set to trigger them are commonly low-frequency and high-severity. They may also be events that may not necessarily have required the filing of a claim in the past (e.g., nontraditional coverage), but have the potential for an economic loss (such as lost sales due to COVID-19).
In many instances where historical information is insufficient, an actuary typically relies on some form of simulation modeling to replicate scenarios of the proposed index. For the property catastrophe market, in which parametric policies are most popular, the actuary will typically utilize the results of a catastrophe model. For other types of triggers, the actuary would need to be provided with some type of information related to the index. For our construction example above, the actuary can be provided with historical weather information and internal financial projections related to weather events. In the retail and healthcare scenarios, the actuary can be provided with internal financial projections, coupled with external economic indices. In other instances, actuaries can research similar coverages, products, or other external information to derive a loss distribution from which a simulation can be run. The more relevant and accurate the data, the better the distribution. Basis risk will also be minimized.
Once a distribution is derived, the actuary can simulate the real-world scenarios and deliver results to tailor-fit the coverage needed, whether it is simply the expected loss or a stop-loss policy based on a higher probability level (e.g., a payout if the losses exceed the 90th probability level).
Figure 3: Actuary Role
Following the results of the simulation and addressing the coverage parameters, the actuary can help develop the policy and coverage forms to be filed with regulators.
Captives are well known for financing unusual and hard to place risks. No matter what industry your captive is in, parametric policies can be utilized to bridge coverage gaps that are difficult to insure with a traditional indemnity policy. While basis risk is a potential downside to parametric insurance, it can be mitigated through dual triggers and modelling by the actuary. Parametric insurance can also be extremely beneficial in the wake of an economic loss, as the policies payout quickly and remove the claim adjustment process, helping to improve cash flow. If you have unusual or hard-to-place risks, reach out to your actuary to see whether a parametric policy is the solution!
2 Captive Insurance Times (March 2, 2022). Pardon the interruption. Retrieved April 21, 2022, from https://www.captiveinsurancetimes.com/specialistfeatures/specialistfeature.php?specialist_id=350&navigationaction=features&newssection=features.
3 NAIC (February 24, 2022). Parametric Disaster Insurance. Retrieved April 21, 2022, from https://content.naic.org/cipr_topics/topic_parametric_disaster_insurance.htm.
4 Swiss Re (August 1, 2018). What is parametric insurance? Retrieved April 21, 2022, from https://corporatesolutions.swissre.com/insights/knowledge/what_is_parametric_insurance.html.
5 Artemis. What are industry loss warranties (ILWs)? Retrieved April 21, 2022, from https://www.artemis.bm/library/what-are-industry-loss-warranties-ilws/#.
7 Hall, C. (May 8, 2021). What is basis risk in insurance and why should I care? FloodFlash. Retrieved April 21, 2022, from https://floodflash.co/what-is-basis-risk-in-insurance-and-why-should-i-care/.
8 Brettler, D. & Gosnear, T. (January 9, 2020). Parametric Insurance Fills Gaps Where Traditional Insurance Falls Short. Insurance Journal. Retrieved April 21, 2022, from https://www.insurancejournal.com/news/international/2020/01/09/553850.htm.