What was done?
We worked alongside actuaries from the client organisations on the design of much needed drought weather-index insurance products for Ethiopia and Madagascar, based on satellite-based, ground and climate re-analysis data. Targeted at small farmers and business owners, these simple and objective insurance products aim to cover the underserved population against natural disasters, exacerbated by climate change.
Context and local challenges:
A particular challenge faced in this project was the scarcity of ground information to assess satellite and reanalysis climatological data and to validate models. Limited data was available for Ethiopia, while in Madagascar ground information suitable for insurance product design was virtually non-existing.
Another challenge had to do with rocky soil conditions in Ethiopia, which impact the accuracy and usability of commonly used satellite-based drought indicators, such as EVI (Enhanced Vegetation Index).
Additionally, in the case of Madagascar, the local practice of planting seeds several times a year, to ‘hedge’ against increased weather volatility, made it harder to establish specific seeding periods to be used as reference for drought product design.
Our strategy to data assessment and selection:
To address the data scarcity challenge and identify climate variables and products which can well replicate local drought conditions and which can be used for subsequent insurance product design, we undertook a correlation and time lag analysis between different precipitation, soil moisture and vegetation index datasets. This was expected to provide insights into wet/dry patterns leading to drought conditions and into the ability of the different products to reproduce historical droughts.
Four precipitation products were included in the analysis, namely IMERG, ARC, TAMSAT and ECMWF’S ERA5. With regards to ground conditions, ESA’s CCI soil moisture product and MODIS’ Enhanced Vegetation Index (EVI) were considered in the analysis.
On the whole, the IMERG and ERA5 precipitation products displayed the best performance, with IMERG performing best at daily scale and ERA5 at monthly scale. These two datasets were then used for insurance product design
Insurance product design:
The design of index-based insurance products entails statistical analysis of relevant climatological variables -with a focus on extremes- to ultimately inform pricing structure. That is, the thresholds at which pay-outs are triggered.
In this phase and based on the selected precipitation products, we used Generalised Extreme Value (GEV) analysis and Standardised Precipitation Index (SPI) for drought characterisation. We worked closely alongside the clients’ actuaries to ensure that an effective, fair and sustainable pricing structure was obtained, accounting for the aforementioned local challenges.