Enhancing crop insurance design in South-Asian agriculture

Miranda Meuwissen (WUR) and Shalika Vyas (CCAFS)

Participants from South Asia and Wageningen University came together to develop a common research agenda for agricultural insurance.

Agricultural insurance is gaining importance in South Asia, making it one of the fastest-growing markets globally. It is part of broader risk management initiatives that deal with recurring climate extremes and food production shocks in the region. At the same time, the advent of new technologies like machine learning, advancements in remote sensing and crop modeling have opened new opportunities for their application in agriculture, although their use in risk management is still limited, especially in South Asia. With this backdrop, a workshop was organized by the South Asia section of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) in partnership with Wageningen University & Research (WUR), to identify key challenges and opportunities for crop insurance research in the region. It was organized as a part of the broader Interdisciplinary Research and Education Fund (INREF) seed money project, aimed to support inter-disciplinary research for agricultural sciences and achieve the Sustainable Development Goals (SDGs).

Identifying key challenges and opportunities

The first day focused on current issues and potential research solutions for crop insurance using different methods like crop modeling, remote sensing, machine learning and innovative economic and financial solutions. Researchers, policymakers and insurance agencies from three countries—India, Sri Lanka and Nepal—gave a brief overview of the crop insurance industry in their countries. The speakers introduced the participants to the national insurance policy and presented case studies for practical knowledge.

Leveraging technological solutions to improve crop insurance design

Organizing crop insurance for millions of farmers is complex. During the two-day workshop researchers from insurance, remote sensing, machine learning and crop modeling met with the insurance industry to discuss the current state of affairs, practical challenges, farmer experiences and research needs. Different stakeholders presented their case studies on the application of technologies to develop and improve current crop insurance schemes. Case studies from economic and finance experts focused on the viability and feasibility of alternative risk financing solutions. The presentations were followed by intensive discussions on Day 2 on how to move ahead—focusing on learnings from North-South collaboration and identifying key research objectives to transform insurance research in South Asia.

Crop insurance as part of SDG action plans

Climate change is expected to exacerbate variability and reduction in agricultural production. For farmers to cope with losses, broad access to insurance is stimulated as part of the SDG action plans. Insurance in agriculture is directly aligned with SDG1 (No Poverty) and SDG13 (Climate Action). By stabilizing farm incomes through insurance pay-offs, it can help in reducing poverty and promoting climate initiatives. It also feeds into SDG2 (Zero Hunger), by ensuring food security under climatic variability and building stable farm incomes.

Thus, insurance can be an effective instrument to provide incentives for good farming practices and risk reduction. However, insurance is still not widely adopted in developing countries due to poor design and implementation challenges. Bio-physical crop modeling and tools of remote sensing and machine learning can play a role to enhance insurance design.

Way forward

In the concluding session of the workshop, six research themes to improve crop insurance design were identified including enhancement of yield predictions at various scales, design of risk profiles and methods to improve loss assessment. Each theme links insurance with up-to-date technological advancements. These themes are the basis for further cooperation between CCAFS South Asia and Wageningen University.