Challenges, solutions in selling agri insurance

In Summary

  • With weather index insurance, there’s a mismatch between a farmer’s experience and their data.
  • To fill the gaps, firm now uses picture-based insurance.

Agriculture insurance comes with its own challenges, such as basis risks.

The use of weather index helps in addressing this.

Muthithi Kinyanjui, business development manager and partnership lead at ACRE-Africa, says they have been distributing weather index insurance, and they were able to remotely monitor farms using satellite data. They also use data from weather stations installed in about 78 farms across the country.

They realized, however, a mismatch between a farmer’s experience and their data.

“There are gaps where a farmer would receive rainfall and our data shows there was no rainfall or the other way round, which is usually worse. This causes a perception gap. We have been trying to fix this through the picture-based model,” Kinyanjui says.

Through the picture-based insurance project, we are able to utilise the village champions and their farmers to capture the actual losses on the ground.

“We are developing a model that is going to help us bridge the gap between the data that we have and the actual farmer’s experience. This will help improve trust among the farmer community and drive demand for insurance products,” she says.

The picture-based insurance is a research project under the Cultivate Africa’s Future programme that is jointly funded by International Development Research Centre and the Australian Centre for International Agricultural Research.


Muthithi explains that village champions are provided with smartphones in which is installed an app called Seeitgrow.

“The village champion has to stand at a specific location and take that exact picture according to the frequency specifications that they have been given whether it is twice, thrice a week for the next three months. The village champion cannot take the picture from any other point for that farm, it has to be at that particular point every season,” she says. 

Muthithi says the champions are trained on all these at the beginning of planting seasons.

She says this is a new model in Africa. In Kenya, it was piloted in Tharaka Nithi, Meru and Embu counties and it is currently being extended to Machakos, Makueni, Busia and Bungoma counties.

It is being implemented by ACRE-Africa in partnership with KALRO, Wageningen University and International Food Policy Research Institute. It has been piloted in India.

Jean Eyase, Project Communication Support from ACRE-Africa, says the picture-based insurance model helps fix the errors faced in the weather index product. 

She says the weather stations service a radius of 10km by 10km so there is bound to be a gap in the data for those farmers that are outside that range.

“So, if we were to squarely use only weather stations and satellite data, then there is basis risk where there are some errors or gaps in the data collected. To fill this gap, we have introduced a picture-based index that combines both data sets and periodic pictures over the season,” Eyase says.

The picture-based index enables the farmer to take accurate pictures of their crop every season and they are given a frequency.

“We then send the pictures we receive from farmers to our credible remote agronomists who analyse them. We have profiled all the farmers and every picture comes under their profile,” she says.

“Once they have analyzed the data, we are now able to correlate the picture-based index and data from weather index to make informed decisions and in triggering customized advisories to farmers.” 

“This work was carried out with financial support from the Australian Centre for International Agriculture Research (ACIAR) and Canada’s International Development Research Centre (IDRC) under the Cultivate Africa’s Future Fund.”