PM crop insurance scheme: Why is it not being implemented effectively and what are possible solutions?

Last week, Shiv Sena chief Uddhav Thackeray had threatened insurance companies under the Pradhan Mantri Fasal Bima Yojana (PMFBY) for not paying the claims to farmers who suffered crop losses.

In reply to a question in Parliament on June 21, the agriculture ministry said insurance firms have approved claims worth Rs 9,473 crore out of a total of Rs 13,471 crore in the 2018 Kharif crop season, The Indian Express has reported. Further, the actual claims paid so far are just Rs 8,540 crore.

As far as 2018-19 Rabi crop is concerned, whose harvest concluded in May this year, the admissible claims “have not yet been worked out in most of the states”.

But, what forms the basis of estimating the claims for crop losses?

Claims for crop losses are assessed on the basis of Crop Cutting Experiments (CCE). The operational guidelines of PMFBY require the state governments to carry out at least four CCEs in every village panchayat and for every crop, the report suggests. The data collected needs to be sent to insurance companies within a month from the date of harvest.

There are around 2.5 lakh gram panchayats in India. This implies, a minimum of 10 lakh CCEs need to be conducted in one season. The numbers are bound to go higher if more than one crop is grown in the same village or even by a single farmer.
What causes the delay in filing claims?

The cumbersome process of conducting so many CCEs over a short duration of time is naturally the primary impediment to the effective implementation of PM Modi’s flagship scheme.

Ideally, insurance firms are supposed to pay claims within two months of receiving CCE data, which estimate yield losses vis-à-vis seven-year average thresholds.

Hence, a delay in sending data by CCEs leads to a delay in processing claims, which ultimately leads to the farmer getting his insurance late.

What is the remedy?

The report has suggested that the use of Automatic Weather Stations (AWS) to collect data instead of conducting CCEs. Costing anything between Rs 50,000 and Rs 1,00,000 each, AWS machines are fundamentally an automated version of traditional weather stations which can be used to measure parametres such as temperature, relative humidity, wind speed and direction and rainfall. They can capture data every 10 minutes and transmit it to remote computers through mobile communication.

How does AWS help assess yield and/or crop failure?

The data collected by an AWS can be a good proxy for crop yield, the report suggests. For instance, a sudden rise in temperature in the month of March is detrimental for the wheat crop. Similarly, below normal rainfall in July-August is bad for most Kharif crops; and high humidity is conducive to pest infestation in the cotton crop.

The report suggests that 80-90 percent can be easily attributed to weather patterns, the data for which can be collected through AWS machines.

Has this been piloted?

The Uttar Pradesh government is in the process of floating tenders for the installation, operation and maintenance of over 2,700 AWS machines. Each of them are supposedly going to be installed on specific locations based on geospatial mapping and would cover an area of 10 square kilometres.

Who manufactures AWS machines in India?

As per the newspaper report, there are an estimated 15,000 AWSs in India. Of these, around 10,000 are operated by private companies such as Skymet, National Collateral Management Services, and Weather Risk Management Services. The rest are operated by the Central and state government departments and universities.

Skymet has installed over 2000 AWS machines in Maharashtra under ‘Mahaved’, a public-private partnership (PPP). It envisages establishing one AWS in every 12 square kilometres for low lands and 5 square kilometres for highlands.