African Risk Capacity in $8m parametric insurance payout to Malawi


The African Risk Capacity (ARC), Africa’s sovereign parametric catastrophe insurance pool, is to make a US$8 million payout to Malawi after its 2015/16 agricultural season parametric drought insurance policy was triggered by ARC’s model.

Initially, the ARC model did not register a payout for Malawi from the drought this year, but the Malawi government had disputed this and requested a re-assessment.

On re-assessment the risk modelling team at ARC found that farmers in the country had switched to use a different type of crop than the model had been calibrated to assume was widely in use in Malawi. Once the drought model was re-calibrated using this crop the parametric policy was triggered and the $8 million payout is now due.

Every policy issued to an African member state by the African Risk Capacity Insurance Company Limited (ARC Ltd) is based on parameters derived from its drought risk model, the Africa RiskView. Each country uses a customised version of the model, to take into account various parameters, including the predominant types of crop grown, in order to ensure the model is senistised to each policy and reflect the country’s historical drought risk profile and current farming practices.

ARC explains what happened in this instance with Malawi:

Malawi bought a parametric drought insurance policy from ARC Ltd for the 2015/16 agricultural season. The policy did not initially trigger a payout, because the model indicated a low number of people affected by the drought. However, the Government’s estimate of the impacted population in Malawi was much higher, suggesting a discrepancy in the results of the model.

ARC investigated the discrepancy through extensive technical work. It first examined the performance of the model as it was originally customised by Malawi, and found that the model had performed as expected given its parameters and the satellite-based rainfall data used. The satellite data was in line with Malawi’s ground-based rainfall data.

Subsequently, ARC conducted extensive fieldwork and household surveys in partnership with Malawian technical experts, including researchers from the Centre for Agricultural and Rural Development (CARD) at the Lilongwe University of Agriculture and Natural Resources (LUANAR).

This work revealed that farmers had switched to a greater extent to growing a different type of crop than that assumed in the model. Farmers shifted in recent years to planting maize with a 90-day growing period, compared to the maize variety with a growing period of 120-140 days as assumed in the customisation of Malawi’s model. The rainfall pattern in 2015/16 was particularly unfavourable to the shorter cycle maize, such that correcting this crop assumption in the model resulted in a very different modelled outcome.

In fact, when ARC re-customised the Africa RiskView to correct this crop assumption, it resulted in the model outcome providing a reasonable representation of the situation on the ground. This in turn triggered a payout under the revised policy to the Government of Malawi.

ARC highlighted “How critical it is to make appropriate and realistic assumptions based on the best-available and current data when customising the model.”

Chair of ARC Ltd Board, Dr. Lars Thunell commented on the payout; “The case of Malawi has showed that heightened attention is necessary in validating national input data provided for the model. Any model’s ability to represent reality depends on the accuracy of starting assumptions and data. Based on the re-customisation using a more accurate assumption on reference crop type, an amended insurance policy was issued to the Government of Malawi and a payout has been triggered.”

Dr. Ngozi Okonjo-Iweala, Chair of the African Risk Capacity Agency Board, added; “ARC was founded by African Governments with the objective of providing them with the tools and capacity to better manage natural disaster risks. ARC Ltd stands by to support Malawi and to continue to help the country develop a comprehensive and effective drought risk management strategy.”

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