African Risk to pay-out $8m for drought after risk model is recalibrated

Mutual insurer African Risk Capacity Insurance Company (ARC) will pay $8.1 million to support the Government of Malawi‘s response to a 2015/16 drought – but only after the parametric model used for assessing whether a pay-out has been triggered was recalibrated.

The pay-out will be released once ARC approves the Government’s plan on how the pay-out will be used in response to those affected by drought in Malawi.

Goodall Gondwe, the Minister of Finance, Economic Planning and Development for Malawi, said: “Malawi welcomes the pay-out from ARC given the significant challenges in securing financing to support the millions of affected households in the country.”

For the 2015/16 agricultural season, Malawi had bought a parametric drought policy from ARC.

In this case, the policy did not initially trigger a pay-out, due to its drought risk model Africa RiskView indicating a low number of people affected by the drought.

In spite of this, the Malawi Government’s estimate of the impacted population was much higher, suggesting a discrepancy in the results of the model.

ARC has since investigated the discrepancy and found that farmers had switched to a greater extent to growing a different type of crop than that assumed in the model.

ARC commented: “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.”

When ARC corrected the crop assumption for the Africa RiskView model, this in turn triggered a pay-out under the revised policy to the Government of Malawi.

Lars Thunell, chair of the board at ARC, stated: “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 pay-out has been triggered.”