determine the average claim payment rate for the district, with this total rate split between village Panchayats or Blocks using high resolution remote sensing imagery or local weather data. As another example, insured farmers could receive a claim payment based on block or district level yield estimates, with potential for a top up if local weather or remote sensing imagery data suggests unusually low local yields.

Third, the insurance unit size could be reduced, for example from the level of the block to the village Panchayat. However, without village Panchayat-level historical data it would not be possible to compute the actuarial premium rates for village Panchayat-level insurance units and so any reduction in insurance unit size would have to be considered to be a ‘social benefit’ paid for by government and not be passed onto the insurer, at least till the time a sufficient data series is created. Any reduction in the insurance unit size would also require a large increase in the number of crop cutting experiments to be conducted from 500,000 to an estimated 5.5 million (Joint Group 2004), and possibly even up to 10 million (author estimates). This may make it challenging to concurrently increase the quality, speed and reliability of crop cutting experiments.

# **4. The pilot modified National Agricultural Insurance Scheme (mNAIS)**

In September 2010, the Government of India approved the modified National Agricultural Insurance Scheme (mNAIS), moving from a social crop insurance program with ad-hoc funding from the Government of India to a market-based crop insurance program with actuarially sound premium rates and product design. Given the technical and operational challenges associated with moving from the NAIS to the mNAIS, implementation began with a three-season pilot, starting with 34 districts across 12 states for the Rabi 2010-11 crop, and scheduled to increase to 50 districts (around a tenth of India). In Rabi 2010-11 approximately 340,000 farmers purchased policies under this scheme, with a premium volume of approximately US$10 million, and over time it could be expanded to India’s 110 million farmer households.

The mNAIS comprises a suite of innovations to NAIS, most notably the move to an actuarial regime, where farmer premiums and government subsidies will both be paid upfront at the start of the crop season to the insurer (Table 4). The insurer, which could be the public insurer AICI or a private sector competitor at the choice of each state, will then be responsible for settling all claims as they fall due. Whilst for Rabi 2010-11 most states have opted for mNAIS cover through the public insurer AICI, two states have selected private insurers and around five international reinsurers are providing substantial reinsurance to the insurance providers, both on an excess of loss and quota share basis. Increasing competition and expanding the role of the private sector in crop insurance contributes to the promotion of effective public-private partnerships in agricultural insurance.

Table 4: Summary comparison between NAIS and mNAIS

|Key Issue|NAIS|modified NAIS|
|---|---|---|
|Public<br>financing|Ex-post subsidy structure leads<br>to open ended fiscal exposure,<br>high variability in annual<br>payments and delay in claims<br>settlement|Ex-ante financing, in the form of upfront premium<br>subsidies. Insurer to receive premiums (farmer<br>collections + premium subsidies from the<br>government) and is responsible for managing the<br>liability of the mNAIS on a sustainable basis,<br>through risk transfer to private reinsurance<br>markets and risk retention through its reserves.|
|Delays in<br>claims|Delay in NAIS claim payments<br>due to the time taken to|Ex-ante financing and streamlined CCE procedure.|

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