Legal considerations
REDUCING BASIS RISK VIA IMPROVED MODELLING
The African Risk Capacity (ARC) is a world leader in parametric trigger modelling and capacity building with its bespoke Africa RiskView tool. ARC’s experience has provided an interesting example of the importance of accurate input data. In 2016, a policy issued to Malawi was not immediately triggered even though there was widespread crop failure. Subsequent investigations by ARC revealed that farmers in Malawi had switched to a different crop with a shorter growing cycle. When this data was put into the model it created a more accurate estimate of the drought-affected population and a payout was triggered. In time, basis risk may be minimised by more detailed and accurate modelling and greater availability of data. Sophisticated parametric triggers for hurricane risks are now designed to respond to a storm’s radius, maximumwind speed, and latitude and longitude at landfall. Another example of innovation in modelling is the Kenya Livestock Insurance Program, supported by the Kenyan government, Swiss Re and the World Bank, which uses satellite images to monitor grazing conditions.When livestock are at risk it delivers parametrically- triggered insurance payments for feed, veterinary medicine and water directly to pastoralists via mobile phones.
Parametric insurance responds to a trigger (e.g. wind speed exceeds a threshold), and the amount payable depends on the modelled outcome of that trigger. So there is an inherent basis risk: the trigger might not cause loss for the insured; or the loss it incurs might not be what was modelled. Of course, conventional insurance does not always fully indemnify the insured for its loss, but the reason is usually more obvious – for example a retention, limit or exclusion. Insurance regulators are understandably keen to see that basis risk is minimised, but it can create uncertainty and damage trust in the insurance sector. Reducing basis risk is particularly important where the policyholder is unsophisticated, or a first-time purchaser of insurance. Accurate modelling is key to ensuring that any gap between losses experienced and parametricpaymentsisassmallaspossible.
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