On 29 August 2026, PIB issued a backgrounder on the Pradhan Mantri Fasal Bima Yojana, subtitled Affordable Crop Insurance for Every Farmer. The headline figures cover Kharif 2016 to Rabi 2025-26: more than 92.46 crore farmer applications insured, over 26.33 crore applications paid claims, and total claims exceeding ₹2.06 lakh crore. The Union Budget 2026-27 allocates ₹12,200 crore.
Note what the ratio in those first two numbers says: roughly 28 per cent of insured applications resulted in a claim payment over the decade. For an insurance product covering weather risk in a monsoon-dependent agriculture, that is a high incidence — which is the point. This is not a product sold against a remote catastrophe; it is one paying out on a regular basis.
Why crop insurance is a hard product to sell, and why the state runs it
Start with the economics, because it explains every design feature of the scheme.
Private crop insurance markets fail almost everywhere, for three reasons a candidate should be able to name:
- Covariate risk. Ordinary insurance works because losses are independent — one house burns while its neighbours do not, so premiums from the many pay the claim of the few. A drought does not work that way. It hits every farmer in the district simultaneously, so the insurer faces one enormous correlated loss instead of many small independent ones. That is very hard to price and to reserve against.
- Adverse selection. If insurance is voluntary, the farmers most likely to buy are those on the most marginal land facing the highest risk — pushing premiums up and driving safer farmers out.
- Moral hazard. An insured farmer has weaker incentive to invest in protecting the crop.
The state's answer to all three is to make the product cheap enough for wide participation, and to subsidise the difference. Wide participation dilutes adverse selection, and public backing absorbs covariate risk that no private balance sheet comfortably holds.
The premium structure is therefore the most examinable element, and it works by capping what the farmer pays:
| Season / crop | Maximum farmer premium (share of sum insured) |
|---|---|
| Kharif food and oilseed crops | 2% |
| Rabi food and oilseed crops | 1.5% |
| Annual commercial and horticultural crops | 5% |
The balance of the actuarial premium is shared between the Centre and the state government. The farmer's contribution is a fixed, low, predictable number; the subsidy absorbs the variance. The ₹12,200 crore budget line is that subsidy.
The release's illustrative case makes the arithmetic vivid: a farmer in Nagaon district, Assam, paid a premium of ₹100 and received ₹50,600 after flood damage — a ratio that is only sustainable because most policies in most years do not claim.
What is covered, and what is not
The covered span is the crop's whole life, which is the scheme's distinguishing feature against older crop insurance:
- Prevented or failed sowing — before the crop exists
- Standing-crop losses from drought, flood, cyclone, hailstorm, pests and disease
- Widespread mid-season adversity
- Localised calamities — hailstorm, inundation, landslide — assessed at the individual land parcel, not the village average
- Specified post-harvest losses from cyclone and unseasonal rain, for a defined window after harvest
The localised-calamity provision is worth understanding, because it addresses the oldest complaint about area-based crop insurance. Traditional schemes paid out on the average yield of a defined area, so a farmer whose own field was destroyed received nothing if the block average held up. Assessing hailstorm, inundation and landslide at the individual land parcel closes that gap.
The exclusions are equally examinable: losses in non-notified areas, losses outside the covered crop lifecycle — before sowing and after the crop leaves the field — and losses from excluded causes.
Who is covered: the loanee/non-loanee distinction
This is the single most likely question from the topic.
- Loanee farmers take seasonal crop loans from banks or hold active, standard Kisan Credit Card accounts. Their premium is deducted automatically from the loan by the bank.
- Non-loanee farmers have no crop loan, or a non-standard KCC-linked loan. They enrol voluntarily.
Enrolment is voluntary for all farmers — the scheme was made optional in 2020, having earlier been compulsory for loanees. The number the release highlights is the meaningful one: across the decade, about 50 per cent of all enrolments have been non-loanee farmers. Voluntary uptake at that share is the strongest available evidence that farmers find the product worth buying rather than merely having it deducted.
Coverage extends to tenant farmers and sharecroppers, subject to insurable interest and documentation — land records, tenure agreements or sowing certificates as prescribed by the state. That qualification matters: a tenant without documentation is precisely the farmer most exposed and least able to prove eligibility, which is where the land-records digitisation agenda intersects with agricultural insurance.
The technology, which is where the real reform happened
The historic weakness of Indian crop insurance was never the promise; it was claim settlement speed. Yield had to be established through Crop Cutting Experiments — physically harvesting sample plots and weighing the output — a process that is slow, manpower-intensive and disputable. A claim settled after the next sowing season has already begun does not solve the problem it exists to solve.
Two systems named in the release address exactly this:
- YES-TECH — the Yield Estimation System based on Technology — uses remote sensing and modelling to estimate yield, reducing dependence on manual crop-cutting.
- WINDS — the Weather Information Network and Data System — builds a denser network of automatic weather stations and rain gauges at block and panchayat level, so weather-indexed triggers rest on local data rather than a distant station.
Why density matters: a weather-index product pays when a measured parameter crosses a threshold — rainfall below a level over a defined window, for instance. If the nearest gauge is fifty kilometres away, the measurement may bear no relation to what fell on the insured field. Denser measurement is what makes index insurance honest, and it is the technical precondition for fast, dispute-free settlement. These mechanisms connect to the wider treatment of risk and inflation and price behaviour in agriculture in the CDS syllabus.
🔑 Revision block
The document. 29 August 2026 — PIB backgrounder, Pradhan Mantri Fasal Bima Yojana: Affordable Crop Insurance for Every Farmer.
Decade totals (Kharif 2016 – Rabi 2025-26). 92.46 crore farmer applications insured · 26.33 crore applications paid claims · claims above ₹2.06 lakh crore · roughly 28% of insured applications received a payout. Budget 2026-27: ₹12,200 crore.
Launch. 18 February 2016, operational from Kharif 2016.
Why private crop insurance fails. Covariate risk — a drought hits every farmer at once, so losses are correlated, not independent · adverse selection — voluntary cover attracts the highest-risk farmers · moral hazard — insurance weakens protective effort. The state's answer is cheap premiums for wide participation, with the difference subsidised.
Premium caps — the key table. Kharif food and oilseed crops 2% · Rabi food and oilseed crops 1.5% · annual commercial and horticultural crops 5% of sum insured. The balance of the actuarial premium is shared between Centre and state.
Coverage span. Prevented/failed sowing → standing crop (drought, flood, cyclone, hailstorm, pests, disease) → widespread mid-season adversity → localised calamities (hailstorm, inundation, landslide) assessed at the individual land parcel → specified post-harvest losses from cyclone and unseasonal rain.
Why the parcel-level clause matters. Area-based schemes paid on the average yield of an area, so a farmer whose own field was destroyed got nothing if the block average held. Parcel-level assessment closes that gap.
Exclusions. Non-notified areas · losses outside the crop lifecycle (before sowing, after removal from the field) · excluded causes.
Loanee versus non-loanee. Loanee — has a seasonal crop loan or active standard KCC; premium deducted automatically by the bank. Non-loanee — no crop loan or a non-standard KCC loan; enrols voluntarily. Enrolment is voluntary for all since 2020. Non-loanees have averaged about 50% of enrolments — evidence of genuine demand.
Inclusion. Covers tenant farmers and sharecroppers, subject to insurable interest and documentation (land records, tenure agreements, sowing certificates).
The technology fix. YES-TECH — Yield Estimation System based on Technology, using remote sensing to cut dependence on manual Crop Cutting Experiments. WINDS — Weather Information Network and Data System, a denser network of automatic weather stations and rain gauges at block and panchayat level.
Why density matters. An index product pays on a measured threshold; a gauge fifty kilometres away may not reflect the insured field. Denser measurement is what makes index insurance honest.
🎯 Practice MCQs
Q1. PMFBY was launched in: (a) February 2016 (b) 2014 (c) 2020 (d) 1999 → (a) — operational from Kharif 2016.
Q2. The maximum premium payable by a farmer for Kharif food crops under PMFBY is: (a) 2% of the sum insured (b) 1.5% (c) 5% (d) 10% → (a) — Rabi is 1.5% and annual commercial/horticultural crops 5%.
Q3. A non-loanee farmer under PMFBY is one who: (a) has no crop loan or a non-standard KCC-linked loan (b) has never farmed before (c) is a tenant (d) is exempt from premium → (a) — such farmers enrol voluntarily.
Q4. YES-TECH is used for: (a) yield estimation using remote sensing (b) weather data collection (c) premium calculation (d) land record digitisation → (a) — WINDS is the weather network.
Q5. Total claims paid under PMFBY over the decade exceeded: (a) ₹2.06 lakh crore (b) ₹12,200 crore (c) ₹50,600 crore (d) ₹92.46 crore → (a).
Q6. 'Covariate risk' in crop insurance means that: (a) losses are correlated across many farmers at once (b) premiums vary by crop (c) yields differ between plots (d) claims are paid in instalments → (a) — which is why private markets struggle.
Q7. Losses from localised calamities such as hailstorm and inundation are assessed at the level of: (a) the individual land parcel (b) the block average (c) the district (d) the state → (a).
Q8. WINDS refers to: (a) Weather Information Network and Data System (b) Wide Insurance Network for Distressed Sowing (c) Water Index for Non-Drought Seasons (d) Weather Index for National Disaster Support → (a).
Q9. Enrolment under PMFBY for loanee farmers became voluntary in: (a) 2020 (b) 2016 (c) 2026 (d) it remains compulsory → (a).
Q10. The traditional method of yield assessment that YES-TECH reduces dependence on is: (a) Crop Cutting Experiments (b) satellite imagery (c) farmer self-declaration (d) mandi arrivals data → (a).
Q11. The share of the actuarial premium above the farmer's capped contribution is borne by: (a) the Centre and the state government (b) the insurance company (c) the farmer's bank (d) NABARD alone → (a).
Q12. Non-loanee farmers have accounted for approximately what share of PMFBY enrolments over the decade? (a) 50% (b) 10% (c) 28% (d) 75% → (a).
📋 How this gets asked (PYQ pattern)
Agricultural-scheme questions come in four shapes. The premium item — the 2 / 1.5 / 5 per cent caps matched to Kharif, Rabi and commercial crops, asked almost verbatim, with the Kharif and Rabi figures the pair most often swapped. The coverage item — whether prevented sowing and post-harvest losses are included, where candidates assume cover begins only at sowing. The technology item — YES-TECH against WINDS, one for yield and one for weather. The launch-year item — 2016 for PMFBY, set against 2014 for PMJDY, 2015 for PMKSY and 2018 for PM-KISAN in a matching set.
The fresh 2026 hook is the decade milestone: 92.46 crore insured applications and ₹2.06 lakh crore in claims. A statement pair on the launch year and non-loanee eligibility is the likeliest single item, with the second half written false. As always, we describe the recurring pattern, not any exact past question.
Preparing for CDS or OTA? Scheme questions are won on the numbers inside the scheme, not the slogan around it — one page of premium caps, launch years and administering ministries covers most of what is asked. Build it with our CDS/OTA economy hub and notes on inflation, follow the daily CDS/OTA current affairs, and prepare with our faculty in the upcoming Cavalier courses in Delhi.
✍️ Written by Hitendra Deswal — Economy & agricultural policy faculty at The Cavalier. Reviewed by the Cavalier Faculty Desk. The Cavalier, founded by ex-Army officers, has trained NDA/CDS/SSB aspirants since 2001 (Facebook · YouTube).
Source: PIB Backgrounder / Ministry of Agriculture & Farmers Welfare, 29 August 2026. Premium structure and scheme features cross-verified with independent sources.