A move towards parametrics in captives

Thomas Keist of Swiss Re discusses the current interest levels in parametric solutions for captives.

Captive Review (CR): What are the interest levels at this time in utilising parametrics within a captive to cover environmental risks?

Thomas Keist (TK): In general, corporates are, at least in principle, more interested in parametrics at this time for two reasons. First, we are in a hard market and therefore prices increase and clients look for alternatives. Second, with respect to capacity, sometimes when you look for  solutions, you might find the capacity you need in parametrics which cannot be found in the traditional marketplace, possibly as a carve-out solution from your property program for specific nat cat perils.

Climate change-related environmental risks are what more enquiries around parametrics are centred on at this time. While these may relate to temperature, precipitation, river water levels, , droughts or floods, the most common risk covered by parametrics is for windstorms and hurricanes.

CR: What are the challenges of placing parametric policies into a captive?

TK: Regarding the captive industry, there has been, in principle, a clear uptick in interest around applying parametric policies within a captive. The problem, however, lies in implementing parametric covers within a captive. This is a more complicated process because the question is: how does the captive transform the coverage they buy on a parametric basis into the coverage of the captive’s insureds?

One thing which is well known regarding parametric insurance, is that you have a so-called basis risk. Of course, captives rely heavily on the indemnity principle, sincethe insureds within the corporate are very much dependent on the indemnification for the losses they are experiencing. However, a parametric cover is not an indemnification. The result of a parametric policy is a fixed payout based on that parametric trigger. Therefore there may well be a difference between what the parametric cover pays and what the loss actually involves on the insureds side. This leads to another question: can the captive pass on that basis risk to the insured? If yes, then the captive, in its coverage towards the insureds, just reflects the basis risk that comes from the parametric cover they buy from the market.

On the other hand, if the basis risk is not acceptable to the insureds, and they want 100% indemnification for the losses they have, the captive might actually act as the transforming entity and, assuming the capitalisation of the captive is large enough, the captive might accept the basis risk coming from the parametric (re)insurance and still provide indemnity insurance on the front end to its insureds — a case of the captive transforming this parametric basis risk into an indemnification coverage. If there is any gap in between — whether the parametric payout is more or less — the captive would itself take the basis risk on.

Once a captive is large and mature enough and diversified enough, it could act as this transforming entity, allowing an efficient parametric insurance buying process while still providing indemnity insurance to its insured. In principle, this is a consideration I see working for captives and parametrics. However, in real practice, I often see that this is a stumbling stone for captives towards buying parametric insurance.

CR: Does the captive industry think of basis risk as more of an obstacle than it truly need to be?

TK: From a theoretical point of view, this is true since basis risk can be greatly mitigated. The better modelled the parametric solution an individual ultimately buys, the lower is the basis risk. And there is more and more means and data to achieve that today. This, however, is just the theory. In practise, buyers of parametric solutions often go for less customized, but bear commoditised, easy to understand solutions. And then one could look at it empirically: how often did the parametric solution – therefore – disappoint? In other words  how often did the corporate suffer a loss yet within the parametric solution coverage was not triggered and didn’t pay out? These considerations feature in practise more prominently in those who have already decided against applying a parametric coverage in their captive.

CR: What other perceived challenges are there around parametrics?

TK: Parametric solutions, although they have been around since the 90s are, in many instances, they are still very ‘rough’ and inexact. “Rough” is to say that parametrics are not deeply sophisticated nor very much customised to specific clients’ risks. Essentially, parametric coverage is viewed as more of a sledgehammer than a reflex hammer, with the reason being that in today’s world, parametric insurance providers make up a small number within the marketplace overall and the entire concept remains niche compared to the huge commercial indemnity based insurance market.

If you are a customer and also typically if you use a broker to place your risk and you decide you want to have a parametric solution, in order to get comparable offers from the market, the parametric does still need to be quite commoditised. An example of this is known as the “cat[astrophe] in a box” windstorm parametric product. With respect to windstorms, this is the most traditional commoditized coverage type. Consider the Gulf of Mexico or the southeast US where many hurricanes strike. A tropical cyclone comes from the east, and you basically draw a circle or a box on the map to define where your exposures are as a corporate. If a hurricane that goes through the box is a certain category as rated by the official agency, a fixed amount is paid out.

Because this is very rough, you can ask 10 insurers to provide you with a quote for this. You say this is the box or the circle, and you need the payouts to be, for example, $100m if it is a category five hurricane. From there, the insurers will give you offers and you can compare the offers and you take the cheapest one. However, since this is a rough quantification, the basis risk is quite high. But the reason it is high is because you want to have comparable quotes. You don’t want to go with only one insurer; you want to have multiple offers. So today’s trade-off is customisation versus number of comparable quotes.

CR: What solution can Swiss Re offer to keep the basis risk low?

TK: A more sophisticated approach we have at Swiss Re is a product called STORM. This product looks at wind speeds at exactly the locations that a client specifies. You can, for example, specify 15 locations by geographical latitude and longitude, and specify the payout amount that should happen for each of these respective locations above a specified windspeed. It’s not just a case of what category a hurricane is but instead is predefined payout at the exact speed of the wind at each covered location.

We use live data from various sources through a 3rd party provider called RMS HWind to provide very precise data points about the speed of wind in a precise location or multiple locations as specified by the client. By doing this, STORM has the advantage that the basis risk becomes very small, although there is also the disadvantage that because there aren’t a large number of insurers offering exactly this product, a client cannot look at directly comparable quotes.

Given a risk manager tends to need to go to the CFO and show them multiple quotes, the choice of choosing a product with the lowest basis risk is hindered and thus this solution becomes undesirable for some because it is more difficult to ‘sell’ internally.

CR: How can a captive become a transformative driver for parametrics?

TK: By having a captive, you have an entity within your corporate which is professionalised on insurance buying and risk management and has all the necessary internal data to come up with the right analysis for both, risk mitigation measures as well as buying the right insurance programme. Because you’re so intimate with the risk of your corporate, you are in the best position to move towards more sophisticated parametric insurance solutions which have a low basis risk.

It is really a chance to further advance the function of a captive, and also better analyse and use the available data and understanding of the scope of these risks to move toward sophisticated solutions like parametric covers.

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