Few significant bottlenecks that are limiting the scaling up of weather- index insurance include lack of reliable weather data, low density of weather stations leading to high basis risk, and limited data on damage and hazard for parametric modelling of the insurance . Several innovations are being tried and tested to overcome the limitations associated with the index insurance which include developing multiscale index insurance, application of remote sensing, smartphone-based near-surface remote sensing and building insurance based on vegetation indices instead of relying on weather data alone . Alternative indices, such as the NDVI, are being tested for their applications in designing index-based insurance in India . Agro-meteorology-based statistical analysis and crop growth modelling have been suggested to calibrate and rectify faulty weather indices . Establishing automatic weather stations can improve data accuracy while preventing the delay in acquiring the weather data . These technological applications have already started finding space within insurance programmes designed by national governments in Asia. For example, the government of India has released new operational guidelines for the application of new technologies such as drones, remote sensing and mobile phone apps in implementation of the national agricultural insurance, which is the third largest insurance in the world .
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