Lack of data, on exposure, historical crop yields and insured losses, pose a challenge in insuring Indian crop risk, according to Lloyd’s of London, global insurance and reinsurance specialist.

A probabilistic crop risk model of the crop insurance market must reflect the way crop insurance is administered, according to Shankar Garigiparthy, Country Manager & CEO, India, Lloyd’s of London.

In an exclusive interview to BusinessLine on the occasion of release of the Lloyd’s report ‘Harvesting Opportunity: Exploring Crop Reinsurance in India’ in association with Risk Management Solutions (RMS), a catastrophe risk modelling company, he said the Pradhan Mantri Fasal Bima Yojana (PMFBY) has helped by reducing premiums for farmers and expanding the coverage of crop insurance.

There are discussions to cover more crops and increase the cropped area coverage to 50 per cent by March 2019 which are great steps to strengthen the scheme further. The typical short tenures may be one area which is going to change in the future,” he added. Excerpts:

What are the desirable attributes of a probabilistic crop risk model for the Indian crop insurance market?

We think this should include the following attributes: Major drivers of crop yield variability, nation-wide coverage for most perils, model for insurance clusters, attritional and catastrophe losses, impact of irrigation, separate models of different crops for Kharif and Rabi seasons and models for PMFBY and weather-based crop insurance scheme, modelling for historical and probabilistic simulated losses and exposure management functionality. A strong crop risk model will provide a valuable tool in understanding and accounting for uncertainty.

The States have been allowed to set up their own insurance companies for PMFBY. Will that be too many ?

We believe that more players in the market is good for the industry and for the farmers. There will be wider participation and we see it as a step in the right direction to increase coverage and protection for farmers.

The national crop insurance data portal requires a greater wealth of data to fully meet the reinsurance market needs. Gathering detailed and real-time exposures at the time of planting (such as crop variety, planting dates, irrigation levels) and better monitoring via remote sensing will help to improve crop risk modelling.

With the availability of better quality data, crop models can become more sophisticated to consider the impact of different managerial practices (such as seed varieties and the use of fertilisers).

Models can also evolve to allow in-season loss prediction by applying forecast weather data to crop yield models, as well as estimating crop yield and loss behaviour under different climate scenarios.

Since no crop is free from threat of weather damage, should not PMFBY re-adjust its goal posts with respect to take-up rates?

The Indian crop reinsurance market is unique. It remains crucial to ensure there is better quality of data input and more risk transparency.

Much of the framework to ensure smooth implementation of the PMFBY is already in place; seamless implementation will ensure greater accuracy and stronger adherence to timelines.

We are confident that the risks of moral hazard and adverse selection are being minimised by the processes set up in PMFBY.

What does PMFBY need to do to reduce the protection gap and ensure financial stability to farmers?

A strong technology-backed platform could help ensure more accurate claim information and claim settlement procedures for farmers. There is also opportunity to increase awareness about the benefits of PMFBY across villages. Wider inclusion of more farmers in the PMFBY net will help reduce the protection gap.

Overall, we feel the industry’s approach to the PMFBY is supportive, and this is evident in the immense growth of the crop insurance market since the scheme’s introduction in 2016.

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