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Keynote 3 Climate Risk and Agriculture - Case of Indian Crop Insurance
KOLLI N RAO, PhD Indian Crop Insurance Industry Expert (IRICS / Aon Benfield)
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OVERVIEW
§ India: The Setting § Insurance Penetration § Crop Insurance: Challenges § Research & Way Forward
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The Setting
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§ 1.2 billion population § Agriculture sustains ~ 70% population § 120 million farm holdings § 62% farmers own less than ONE hectare § 145 million hectares of cultivated land § 1.16 Hectare Average Farm-holding size § 50% of area under cereals and millets § Agrl. GDP estimated at US $ 285 billions (FAO, 2010) § Nearly 3/4th Rainfall received over FOUR months § Disparity in the rainfall distribution is so great – droughts and
floods occur at different parts of the country at the same period and in the same place at different periods
§ 1/3rd country is mostly under threat of drought § 1/6th country prone to floods
Indian Agriculture: The Setting
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India: Architecture of Crop Insurance Implementation • Almost 100% INDEX insurance • YIELD index and WEATHER index dominate • Credit linkage, and mandatory for borrowing farmers • Risk covered is based on production cost (safety-net) • Insurance acts as collateral, and lending agencies have the first
lien on claim • Minimal distribution costs • Claims process is automated • Yield estimation is done by the provincial government agencies ,
and based on ‘single series’ • Weather data comes from both public as well as private data
providers • Private insurance providers (9) are allowed, and enjoy same
level of government support as Public Insurance Company (AICI)
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Insurance Penetration
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Index Insurance: Numbers 2012-13
Note: 1.The sum Insured and premium size for 2013-14 is expected at US $ 12.5 billion and US $ 800 million, respectively 1.The sum Insured and premium size for 2014-15 is expected at US $ 15 billion and US $ 1.30 billion, respectively
ProgramFarmers (Millions)
Hectares (Millions)
Sum Insured (US $ Millions)
Premium (US $ Millions)
Program Nature
NAIS 15.45 29.92 5892.35 195.67 Adminstered
WBCIS 13.23 18.39 4038.47 379.45 Actuarial
MNAIS 2.98 2.97 1149.20 125.10 Actuarial
TOTAL 31.66 51.28 11080.02 700.22Source: Government of India NAIS Figures are Provisional (AIC)
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Research Findings
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Research Findings
§ Weather Index products analyzed across the competing insurance providers show significant differences in product design, pricing approach, and benefits offered
§ The correlation appears better for Kharif products where rainfall is the key component, and the Weather Index product is underpaying. In comparison, Rabi products, particularly the heat (temperature) parameter show a poor correlation between weather and yield, and Weather Index product often overpaying
§ 42% probability of Weather Index products giving payout with NO visible Yield loss; Only 73% probability of Weather Index products giving payouts when Yield loss is 100%
§ Spatial basis risk arising out of lack of adequate density of weather stations appears significant for rainfall
§ The present Weather Index product is complex and fares poorly as an insurance mechanism. The payouts ate too frequent and too small
§ Farmers practicing crop production under irrigated conditions have shown higher interest in crop insurance
§ The awareness about crop insurance is primarily driven by the level of education, size of landholding and type of farming
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Challenges
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Key Gaps and Challenges of Index Insurance
General § Lack of Insurance culture § Parallel government programs § Full Value not insured (under insurance) § Localized losses
Yield Index § Larger Insurance Unit size and Basis Risk § Lack of historical yield data at a ‘smaller unit’level § Yield estimations prone to manipulation and local politics § Large number of Yield estimation surveys & Quality issues § Delayed claim settlement
Weather Index § Too small and too frequent payouts § Lack of Structured approach to Product design § Basis risk: Spatial and Product § Product targeting Micro level § Pricing and Weather Cycles
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Some Technical / Research Solutions … Yield Index § Yield Audit systems (GPS enabled equipment to record key
processes, near real-time reporting of results) § Use of Satellite Imagery to estimate yields (either to corroborate /
peer monitoring / replace manual yield estimations) § Use of Technology to down-scale historical yields (sub-district to
cluster of villages for major crops for past 10 years) § Savings linked insurance products (for promoting loyalty of farmers) Weather Index § Crop Growth Models § Agro-Climatic zone level Crop-wise Product Templates § Standardization of Weather Equipment and Maintenance § Virtual Weather station network at micro level § Double Trigger Products § Index Plus Products