Leveraging Remote Sensing Technologies to Address Incomplete Markets in Crop Insurance

Abstract

In many agrarian economies, crop insurance schemes are the most prominent among government schemes meant to protect agriculture from the vagaries of nature. A market-based solution for insurance that transfers risks from farmers to insurers has been evasive despite decades of public sector encouragement and funding. The situation of low penetration and unprofitable insurers could be termed an ‘incomplete market’ and may be attributed to information asymmetry. With technological advancements in agricultural monitoring and using large scale open-source data about biophysical variables, it has become possible to estimate crop yields and losses at a farm field level. By using objectively collected data from earth observation satellites and weather stations, such estimates can reduce the information asymmetry. We present a prototype of an integrated system that has shown promising results for wheat crop in north Indian plains. Obstacles related to ground (in-situ) data availability and model refinement are to be overcome before the solution is practically implemented. Concerted efforts towards this are warranted from governments, industry and academia to build tech-enabled actuarial models that correctly assess risks in local conditions.