FAQ's

What is parametric insurance?


Parametric insurance is insurance that pays a pre-defined lump sum when an agreed trigger is met. For example, a policy might define a payment of $10,000 when flood water reaches a certain height. Other triggers might be hailstones that fall with a certain diameter that is known to cause dents to car bodywork, or windspeeds that reach a level that is known to cause trees to fall, roof cladding to blow away and power to fail. Parametric insurance policies have been around for at least 30 years in their current form and but they have mostly been used by large corporations and governments.




What at the advantages of predictive parametric insurance?


There are many advantages of predictive parametric insurance. Many of these advantages are shared with standard parametric insurance policies. Payments happen instantly. The Exante Trigger System constantly monitors trigger data sources like weather forecasts and financial data. Once a trigger is met, the payment is automatically made. There is no claims handling process. Exante policy holders do not have to call up to file a claim, and there is no loss adjustment or indemnification process. It's faster for the policy holder, and cheaper for the insurer. No disagreements over payments. Well defined triggers mean there is no confusion or doubt about when or how much to pay. Once a trigger is met, the policy holder always receive the full payment. If a trigger is not met, no payment will be made. This means no lengthy legal battles over payments. Predictive parametric insurance has some unique benefits: Overall loss is reduced. If a policy holder can receive a speedy payment before a loss event occurs, they can act to reduce the total loss. For example, a motorist can move their car to a safe, sheltered car park to protect it from flooding. This may cost the policy holder a small amount during the flood, but will prevent a much larger loss if the car is destroyed. New risks can be covered. Evacuation and preparation for a hurricane can have significant costs. Fueling the car, protecting the home, stocking up on food or vital equipment are all necessary before the storm arrives. If the storm changes direction, or reduces in intensity, these costs do not go away. A predictive parametric insurance policy that pays out before the storm arrives can cover these costs where no other policy can.




What triggers are used for predictive parametric insurance?


Anything can be used as a parametric trigger if it is objective and independent of the insurance company and the policy holder. Windspeed, water height, hours of sunshine, and flight delays are all currently protected by parametric insurance. For predictive parametric triggers, the added restriction is that the data source shows a correlation to the underlying risk. The wind speed forecast is highly correlated with the actual wind that blows at a particular location, so it would make a good predictive parametric trigger for wind related losses. The same wind speed forecast would not correlate very well with flooding risk, so it would be consdered a poor parametric trigger for flood related losses.




Is parametric insurance going to replace normal insurance?


No, we don't think so. We see parametric insurance as complimentary service to traditional indemnified insurance, not as an alternative. Traditional insurance is perfect for covering uncertain losses when the insurer can take time to calculate those losses. Parametric insurance is good for filling in the gaps and helping with short term losses.




What is Predictive Parametric Insurance?


Predictive Parametirc Insurance takes the concept of Parametric insurance once step further. Instead of paying out when a trigger is met, Exante can pay out when the forecast of a trigger reaches a certain liklihood. For example, instead of waiting for flood water to reach 6m above datum, and paying out to cover damages, Exante could see the rainfall or storm surge forecast expects flooding to reach 6m, and pay out days before any damage occurs.





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