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Impact Case Study: 
2017-2024 Journey with Parametric Insurance targeting economically poor flood vulnerable farmers

What was Practical Action grappling with 2017?

With accelerating climate losses, the development community led by several key donors were looking to the insurance industry to develop suitable market mechanisms to compensate those impacted. In 2016 several donors came together to establish the Insuresilience Global Partnership and following implementation of pilot projects, this evolved into the Global Shield launched in 2021 at COP26. However, one of the problems with these initiatives is that they have adopted a very research learning focus with an emphasis on large scale programmes and the establishment of sovereign risk pools.

For Practical Action (PA), insurance is not about developing insurance products, it must be about protecting the wellbeing and security of the livelihoods of the poorest and most climate vulnerable people.  We started to explore insurance from the bottom up. By working with the communities, that we are already working with, we are able to try to unlock what would make insurance work for people living in poverty, those who are most impacted by hazards that are escalating as climate change increases. So, we started by looking at which are the critical assets and which are the critical hazards to determine whether a parametric approach would be feasible. But we did not just need to understand the asset and the hazard, but also the financial contribution of the asset to people’s wellbeing and the coping strategies[1] that are in place to protect this asset from the identified hazard.

[1] Note: If coping strategies are functioning effectively then insurance is probably not needed, however as climate impacts increase many of these coping strategies are becoming erosive, leading to a reversal of development gains. It is in this situation that an insurance product may be worth exploring.

What is parametric insurance? What is Index based Insurance?

Parametric insurance (PI), also known as index-based insurance (IBI), provides pre-specified payouts based on the occurrence of a triggering event, such as an earthquake or flood, rather than indemnifying the actual loss incurred.

This is why long-term data sets to build models are necessary to facilitate the payouts being closer to the actual loss. IBI relies on objective data to determine when the payout is triggered, allowing for faster and more transparent claims processing.

 

A bus navigating the Rocky Roads of Nepal, where rock partially covers the road

PI differs from traditional indemnity insurance which reimburses the insured for the actual loss incurred from events such as floods or storms. This can take time to payout and can be a more expensive product than IBI (Swiss Re, 2023).

In this case study, we refer to index-based meso level insurance (aggregators in the form of intermediaries who are group policy holders on behalf of farmers) for rice paddies.

A bus navigating the Rocky Roads of Nepal, where rock partially covers the road

Durham University PhD research provides hypothetical insurance analysis 2018-2021

In 2018, Colin McQuistan, Head of Climate & Resilience of Practical Action (PA) UK approached Professor Julian Williams, the Executive Director of the Institute of Hazard, Risk and Resilience (IHRR) at Durham University. They explored the feasibility of a collaborative three-year PhD research project exploring parametric index-based insurance as a possible risk transfer mechanism in Nepal for very poor farmers in flood prone areas of the Lower Karnali River basin in Nepal.

Durham University Business School (DUBS) and the IHRR selected Eleftheria Vavadaki as the PhD scholar and her PhD funding was from an alumnus donor and DU Collingwood College. In her IHRR interdisciplinary research, Eleftheria Vavadaki conducted a mixed method approach in her PhD using quantitative data (supervised by DUBS) and qualitative data (supervised by Dept of Geography). PA Nepal selected the Karnali River basin (the Zurich project area) in order to build on existing local partnerships and almost a decade of data from local communities regarding their physical risks. PA Nepal facilitated Eleftheria’s research on the ground (see PA 2024a, 4).

Credit: Bikram Rana, April 2017 Nepal.

The PhD research (2018-2021) helped to clarify the existing barriers to insurance provision. Vavadaki (2021) identified a large potential audience for a parametric insurance product and suitability with the Government of Nepal’s Weather Index Insurance Policy approved by the National Insurance Authority. She focused on flood risk of agricultural crops. Vavadaki conducted a quantitative survey of 705 people and developed a game to test the suitability of insurance and to understand community perceptions of insurance and whether they as farmers would be willing to purchase a product. From Vavadaki’s quantitative and qualitative analysis (see Vavadaki 2021, 171), this figure below shows the key factors affecting demand for IBFI:

Figure 1: Factors affecting demand in the two approaches (Vavadaki 2021, 171)

 

Research Conclusion

In summary, Eleftheria’s research concluded that the following individual factors appeared to influence farmers’ decisions to consider insurance:  

  1. Their perception of flood risk,
  2. Education level of farmers,
  3. Recent weather conditions and whether they had suffered losses and lastly,
  4. Distance and familiarity to the insurance provider.

 

 

Eleftheria Vavadaki and Bikram Rana consider where the local community was flooded.

What happened next? What did PA get out of the PhD?

Practical Action designed and implemented the Index-Based Flood Insurance (IBFI) project from 2021 to 2024 (during the COVID pandemic), with financial support from Insurance Solutions Fund (ISF) and Z-Zurich Foundation...

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