The beauty of parametric insurance solutions is their ability to make natural catastrophe risk management simple and predictable for covered programs of all sizes. So, why does evaluating these solutions so frequently devolve into mind-numbing complications? You can cut through most of the complexity and acquire clarity on the value a given parametric solution will – or will not – bring by going through the following five questions.
What is parametric insurance?
Parametric insurance works using a clearly defined parameter – i.e. a metric or an index that is easy to determine. That can be in terms of the trigger of the insurance, the payout, or both.
Parametric insurance is an insurance program that is triggered, and/or paid very simply using an index rather than words. Currently, parametric is mostly used in the reinsurance space around catastrophe risks, but some risk managers have started to use parametric in the travel, retail and agricultural sectors.
What is the source of the event data?
A “cat-in-a-circle” structure, also known as a “first-generation” structure, triggers when an event of a specific severity (e.g., a magnitude 7.2 earthquake) occurs in a specific geographic area, or a local intensity-based structure, also known as a “second generation” trigger, pays when the hazard reaches a specific intensity at a specific location (For example, at the site, peak spectral acceleration of 0.60g), as measured and reported by an agreed-upon agency or instrument.
In general, first-generation triggers from a reputable scientific agency based on event severity (e.g., moment magnitude of an earthquake or maximum wind speed associated with a storm) provide your program with reliability, transparency, and assurance.
Second-generation parameters are obtained from complicated geographic models and increase uncertainty and complexity, particularly when the model is a black box or private recording instrument. You must ask yourself, “Do I comprehend that ambiguity sufficiently to include it in my solution?”
The third factor to examine is uniformity. Ideally, all of the solutions you’re considering should be triggered by the same publicly available data, such as that provided by the National Hurricane Center, the US Geological Survey, or another global organization. It’s impossible to make an apples-to-apples comparison if they don’t. (And, if you use publicly available data, you always have the same date and don’t have to wait for someone to tell you whether or not an event-triggered your coverage).
Both first- and second-generation triggers may be customized to offer the coverage you want; but, when you add the uncertainty that comes with second-generation triggers, the coverage becomes more opaque. It’s always best to keep things simple, uniform, and transparent.
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How will a planned structure respond to loss events in the past and in the future?
Discussing different payout models with different carriers adds to the complexity. For wind speeds of 100, 105, and 110 mph, one structure may pay differently. Another presents a completely different scenario, in which rewards are determined by the storm type, allowing for greater wind speed variations. Comparing the two options can be tough.
The playing field is suddenly leveled if you just inquire how the proposed arrangements would pay off against specific historical (and fictional) situations. You have the clarity required to compare and contrast two structures.
How does the pricing stack up?
You can readily put a price into context if you view past payouts. Any cost outliers should raise suspicion. While carriers that charge a higher price are frequently questioned, carriers that charge a much lower price should also explain their reasoning.
Remember that the projected loss is the most expensive component of a premium; thus, any significant change in premium is almost certainly due to a significant difference in expected loss. After you’ve figured out how much coverage each option offers, inquire about the estimated loss payouts from each carrier. Cheaper isn’t always better, especially if it comes with shoddy or insufficient coverage.
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What is the best way to put basis risk into context?
Every insurance option entails some level of risk. In a parametric cover, the basis risk is different than in an indemnity solution. Losses under the deductible, over limits, policy exclusions, or vagaries brought on by the adjustment procedure are not covered by an indemnity solution.
The only difference with parametric insurance is that what is covered and what is not is understood and stated explicitly in the policy (e.g., no payout for a Category 1 storm, or an earthquake less than magnitude 6). The important question is where you want coverage: for quick payment to get your firm back up and running, for incidents that would interrupt your staff, or for other gaps in your indemnity policy.
Request that the carriers and brokers assess a proposed parametric solution in combination with your indemnification policy, and then fine-tune it to meet your risk management goals. Understanding basis risk is a good goal, but don’t let it get in the way of a good parametric insurance plan.
Is the wording of the policy simple or complex?
Policy wording reflects how complex (or easy) a carrier’s coverage and claims response will be, from loss definitions and exclusions to payment schedules and third-party involvement. How much paperwork is required? How long will it take for claims to be paid? Is there an additional adjustment that needs to be made after some time? In previous events, how has the carrier compensated for losses? Make sure that all of this information is clear so that you know exactly what you’re getting into.