Dr. Kolli Rao of Aon Benfield/IRICS presented on index-based crop insurance in India at the workshop on Mobilizing a CGIAR Agricultural Insurance Community in Washington, DC, 20-22 January 2014, hosted by the International Food Policy Research Institute and the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Read more about CCAFS work on index-based weather insurance: http://bit.ly/Ll7Z7Z

1. Keynote 3
Climate Risk and Agriculture
- Case of Indian Crop Insurance
KOLLI N RAO, PhD
Indian Crop Insurance Industry Expert
(IRICS / Aon Benfield)

2. OVERVIEW
§ India: The Setting
§ Insurance Penetration
§ Crop Insurance: Challenges
§ Research & Way Forward
2

3. The Setting
3

4. Indian Agriculture: The Setting
§ 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
4

5. 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)
5

6. Insurance Penetration
6

7. Index Insurance: Numbers 2012-13
Program
Farmers
Hectares
Sum
Insured
Premium
Program
(Millions) (Millions) (US
$
Millions) (US
$
Millions)
Nature
NAIS
15.45
29.92
5892.35
195.67
Adminstered
WBCIS
13.23
18.39
4038.47
379.45
Actuarial
2.97
1149.20
125.10
Actuarial
51.28
11080.02
700.22
MNAIS
2.98
TOTAL
31.66
Source:
Government
of
India
Note:
NAIS
Figures
are
Provisional
(AIC)
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

8. Research Findings
8

9. 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
9

10. Challenges
10

11. 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
11

12. 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