Mitigating basis risk in weather index-based crop insurance: harnessing models and big data to enable climate-resiliant agriculture in India

Livelihoods of millions of smallholder farmers across the developing world are under threat from extreme weather events, such as droughts, floods, and heatwaves, with risks projected to increase significantly in future years due to climate change. Crop insurance protects farmers against financial risks posed by extreme weather events, and has been widely advocated as a tool to help farmer households to escape poverty traps and invest in climate-smart high-productivity agriculture. Yet, to date, the success and uptake of crop insurance schemes across the developing world has been extremely limited.

Several reasons can be identified for problems in scaling crop insurance in developing countries. Traditional indemnity-based insurance schemes require time-consuming verification of actual losses experienced by individual farmers resulting in high transaction costs, claims disputes and delays that deter farmers from purchasing insurance. To counteract these issues, governments and insurers seek to develop more cost-effective and reliable tools to determine when, and at what level, insurance should payout to farmers if an extreme weather event occurs. Parametric insurance, for example weather index-based insurance, triggers payouts based on pre-established relationships between meteorological indices and crop yields, removing the need for expensive crop loss assessments. However, a major challenge for current weather index-based insurance is that payouts often are poorly correlated with farmers' actual yield losses, a problem known as 'basis risk', creating a major barrier to use of index insurance for climate risk mitigation.

In this context, how can scientists contribute to the design of smarter index insurance products that meet the needs of farmers, insurers, and governments? The overall aim of this project is to improve the current poor performance of index-based crop insurance by using state-of-the-art environmental modelling and big datasets to reduce basis risk and better protect farmers against weather risks. Our proposed research will develop novel weather index-based insurance contracts that reliably and accurately predict weather-related crop yield losses by combining crop growth modelling, satellite and smartphone imagery of crop growth status, and high-resolution gridded estimates of spatial weather variability. Importantly, our work will produce novel tools and approaches that address two stated needs of the index insurance sector: (i) to reduce temporal basis risk by designing weather index triggers that reflect accurately how yield sensitivity to extreme events varies during the growing season, and (ii) to minimise spatial basis risk by exploiting datasets that capture spatial heterogeneity in weather conditions, crop development, field conditions and management practices.

Working in collaboration with HDFC ERGO General Insurance, a major provider of weather index-based insurance for smallholder farmers across India, we will apply these approaches to design and test new weather index-based insurance products to protect farmers in the major agricultural states of Punjab and Haryana - the breadbasket of India - against combined production risks from extreme temperature and heavy rainfall events. Leveraging unique field data collected through the recent IFPRI-HDFC Picture-Based Crop Insurance (PBI) Project, we will conduct agro-economic impact evaluations to quantify reductions in basis risk, increases in farmer welfare and demand for insurance from our new contracts relative to both current index insurance products and government area-yield insurance schemes. Our work will contribute directly to improvements in the quality of index insurance for farmers in India, and, more broadly, will provide the scientific foundations for weather index-based insurance to more effectively support climate-smart smallholder agriculture across the developing world.

Planned Impact
The main beneficiaries of our work will be: (1) our practitioner partner - HDFC ERGO General Insurance, (2) farmers in India, (3) state governments and the national government in India, (4) the global research and practitioner community in the field of index insurance design. How each group will benefit is outlined below.

HDFC ERGO General Insurance will benefit directly from the development of new weather index insurance products that have lower levels of basis risk relative to their current portfolio of index insurance products. Reduced basis risk will lead to greater demand from farmers for these products, as payouts will be better matched to actual losses experienced by producers. Benefits for HDFC will also extend beyond our specific case study application, and will greatly enhance the company's competitiveness in the Indian crop insurance sector, which has a potential market of over 100 million farmer households and is increasingly focused on using new technologies to strengthen weather index-based insurance as an alternative to traditional area-yield contracts.

Farmers in our study area of Northwest India will be impacted positively through access to higher quality weather index insurance products that capture more reliably the relationship between extreme weather events and crop yield losses. These improved insurance products will reduce farmers' exposure to weather and climate risks, increasing farmers' trust in index insurance and demand for these products. Importantly, greater uptake of reliable crop insurance will also provide the enabling conditions for farmers to access credit to invest in high-productivity agricultural production practices, enabling households to raise average incomes, escape poverty traps, and enhance long-term resilience to climate change. More broadly, farmers beyond our study area will also benefit in the long-term through uptake and implementation of methods for improved index insurance contracts for other crops and in other regions of India and the developing world.

State governments and the national government in India will benefit from exposure and access to novel approaches for developing reliable and affordable weather index insurance products. Expansion of index-based crop insurance is a key pillar of Indian government policy to increase farmers' resilience to weather extremes and climate change, but current schemes have suffered from low voluntary uptake due to poor correlation between weather indices and yield losses. Improvements in the performance of index insurance schemes therefore have the potential to increase significantly farmer uptake of weather index insurance, reduce reliance on expensive loss assessments and subsidies associated with traditional area-yield indemnity insurance, and stimulate growth and development of the wider Indian economy.

The global research and practitioner community in the field of index insurance design will benefit from the development of state-of-the-art tools and methods to implement crop growth models and big datasets within index contract design. Furthermore, these groups will also benefit from improved understanding about the relative potential of these technologies to deliver reductions in basis risk, which will play an important role in guiding efforts to maximise uptake of weather index-based insurance for climate risk management and poverty alleviation in agriculture-based communities across the developing world.