Agriculture Insurance in India

Crop Insurance market in India

• 25 million out of 120 million farmers (20%) are insured under crop insurance schemes

• 90% are loanee farmers. 10% penetration among non-loanee farmers• 2011-12 Weather Index Insurance – Perhaps the World’s largest weather-

based crop insurance programme. 12 million farmers covered - Implemented in 16 states.

• Area Yield Index Insurance - World’s largest Crop insurance programme, 18-20 million farmers covered Implemented in 25 states.

• Government of India targets doubling the farmers’ coverage during 12th plan from 25 million to 50 million.

Background

• Area Yield Approach suggested back in 50’s– Provinces mooted a proposal requesting GoI for financial assistance in

the early 1960s.

• Ministry of Food & Agriculture - examined the feasibility of crop insurance – Circulated a draft scheme to all the States – Not favored by states due to paucity of fund

• Elaborate administrative machinery not available & paucity of resources – Each insured area to be divided into blocks with one Crop Insurance Inspector and 10 crop insurance sub inspectors.

• Geographically homogeneous regions – Difficulty in delineating - absence of data on area-wise farming practices.

Background

• GoI introduced a Crop Insurance Bill & a Model Scheme of Crop Insurance – referred to Dharam Narain Committee – stalled the progress.

• Grounds – More emphasis on elements on “individual approach”

• Breakdown of insurance principle – “ The number of claimants turns out to be nearly as large as that of the premium paying farmers”

Background

• Admittedly, we came to consider it as second best as we found a crop insurance based on ‘individual approach totally impractical. Now, instead of making it impractical by importing into it elements of individual approach, we should accept it as the second best and agree to give it a fair trial”- Dandekar

Background

• Mid 1980s onwards - Studies reflecting the dismal performance of all risk crop insurance programmes world-wide- Rainfall insurance suggested as a response to the unsatisfactory performance of crop insurance in the past decades.

• CCIS in early Eighties• Modified into NAIS late nineties– A separate company constituted to implement the

scheme• Further modified in 2010 as MNAIS

– MNAIS is an Insurance Product and not a scheme

Background

• World Bank (1992) – Drought insurance scheme for all rural households – All insured to pay the same premium and receive the same indemnity per unit of sum insured.

• Pioneering work by J.S. Chakravarti (1920). • No insurance authority could ever maintain a supervising

agency which would be able to watch and enforce that every insured field receives the required amount of care and attention at the hands of its cultivator. Unless some method can be devised by which this great difficulty is eliminated , a system of crop insurance would indeed be impossible”.

Background

• “ A famine in India does not mean grain famine but money famine due to enforced unemployment of agriculturist owing to unfavorable seasonal conditions. An effective system of agricultural insurance by insuring the peasantry against serious pecuniary loss in respect of agricultural operations will render the country less liable to the ravages of famine. In this sense and to this extent agricultural insurance will also be famine insurance”

• First Weather Insurance product launched by private sector as an Insurance product

• Govt. allocated subsidy to weather insurance

Present State : Area Yield Index Insurance

• Area yield based approach. • Covers –Crops subject to availability of past yield data (10 years). • Mandatory for borrowing farmers/voluntary for others. • Capped premiums for FCOS (1.5-3.5 % of SI) and Actuarial rates for

ACH crops. • Yields measured through Stipulated Minimum Crop Cutting

Experiments (CCEs). • Ex-post financing for claims processing. (Not applicable in the

modified version)• Guaranteed yield – 60%/80%/90% of past 3/5 yrs avg. • Sum Insured - amount of bank finance / value of guaranteed yield/

150% of the value of Average Yield.

Area Yield Index Insurance

• Guaranteed Yield TY = 3 year/5 year moving average yield X IL. • Linear trend resulting in low coverage and high premium rates. • Unusually good or bad years have high impact • Unrealistic uniform ILs/premium rates across the state.

• Low coverage levels in areas with continuous adverse seasons. • Overstatement of yield in good years will increase premium

rates despite low payment of indemnity. • Modifications

• Detrended yield data • Moving Average Last 7 years yield data (excluding 2 calamity yrs).

MNAIS: Improvements over NAISDrawback in NAIS Improvements in MNAIS Basis Risk – Geographic: Block taken as insurance unit.

Reduction in insurance unit to GP/ village for major crops. Assessment of claims based on individual basis for localized calamities –hailstorm & landslide.

Basis Risk – Product Coverage No preventive sowing or post-harvest cover

Coverage of prevented sowing (upto 25% (of sum insured). Coverage for and post harvest losses (available upto 14 days from harvest for crop lying in ‘cut & spread’ condition only).

Basis Risk – Product Design Minimum Indemnity Level of 60%. Threshold yield of last 5 years to be taken into account. No exclusion of calamity year.

More attractive guaranteed yields. Threshold yield based on average yield of the preceding 7 years excluding upto 2 calamity years Minimum Indemnity Level (IL) raised to 70%.

Delay in settlement of Claims: No on-account payment. Claim payment more than 12 months from end of cover period.

On-account payment upto 25% advance of likely claims as immediate relief (if the estimated crop losses is more than 50% as compared to normal) Payment of upfront premium subsidy by State and Central Governments.

WBCIS – Business Spread

2 mio0.1

mio

15-18 mio 150 mio

3-4 mio

90 mio

0.2 mio

5-6 mio

1-2mio

5-6 mio

70 mio

3-4 mio

4-5 mio

High

Low

6-8 mio

In terms of premium in $ mn

State Specific PeculiaritiesState Issues Regarding Products Data Status

RajasthanHigh Frequency products. Termsheets are defined by the government. Major risk is drought for Kharif program and temperature for Rabi program.

Good quality historical data. Large spread of settlement stations

BiharAggressive strikes. Multiple iterations on the product. Drought in Kharif and high temperature covers in Rabi are aggressive. Poor quality of data hinders pricing.

Poor quality historical data. Large spread of settlement stations.

Karnataka10 yr BPR should be at least 60% Product contours are not suggested by govt. Government also doesn’t define sum insured breakup among perils.

Good quality historical data. Good settlement station spread.

TamilnaduCriteria similar to that of Karnataka but with BPR of around 5-6 years. Due to merging of two monsoons, large variations in rainfall exist.

Good quality historical data. Reasonable Settlement station network.

HaryanaGovt suggests strike but allows insurance companies to define notional as well as second strikes. High temperature is major risk in Rabi.

Reasonable data but with significant data gaps. Reasonable station network

Chattisgarh Government provides the product details. Insurance companies can choose to take it or leave it

Poor quality historical data. Inadequate settlement station network

AP Govt supports only PSU insurer. Business underwritten only through AIC Data Quality is good

Jharkhand Historical data of poor quality. Govt gives leeway in product design and pricing

Data quality is very poor with most stations having large data gaps

WBCIS – Market

$ 360 mn - Current weather insurance market

$ 800 mn weather insurance market

$ 200 mn weather insurance market

• States on the borderline bring more districts under WBCIS• More states bring horticulture crops under WBCIS• More competition pulls up the non loanee market

• States on the border line substitute WBCIS with MNAIS or NAIS • WBCIS claim ratios remain too low and the payoffs do not

cover actual losses• States decide to reduce its subsidy burden by opting for

MNAIS

Rajasthan TermsheetSTATE- RAJASTHAN DISTRICT Dausa All Tahsil

CROP -Bajra REFERENCE WEATHER STATION AS PER NOTIFICATION UNIT:/ HEC. DEFICIT RAINFALL

PHASE I PHASE II PHASE III

RAINFALL VOLUME

PERIOD 01-July to 20 July 21 JUL TO -20 AUG 21 AUG TO 30 SEPT.

INDEX Aggregate of rainfall over respective PhasesSTRIKE I(<) 60 160 60STRIKE II(<) 30 80 30EXIT 0 0 0RATE I (Rs./mm) 13.33 9.17 13.33RATE II (Rs./mm) 26.67 18.33 26.67MAXIMUM PAYOUT (Rs.) 1200.00 2200.00 1200.00TOTAL PAYOUT (Rs.) 4600.00

PERIOD 01 JUL TO 10 SEPT

RAINFALL DISTRIBUTION (Single pay out)

INDEX Number of the days in a spell of Consecutive dry days.STRIKE (=>) 20EXIT 72PAYOUT PER DAY(Rs.) 38.46TOTAL PAYOUT (Rs.) 2000

EXCESS RAINFALL (Singal Payout)

INDEXMaximum of 3 consecutive day's cumulative rainfall in respective Phases PHASE I PHASE II PHASE III

PERIOD 01-July to 20 July 21 JUL TO -20 AUG 21 AUG TO 30 SEPT.STRIKE I(>) 90 115 80STRIKE II(>) 245 257.5 240EXIT 400 400 400RATE I(Rs./mm) 2.58 5.15 2.50RATE II(Rs./mm) 5.16 10.29 5.00MAXIMUM PAYOUT (Rs.) 1200.00 2200.00 1200.00TOTAL PAYOUT (Rs.) 4600.00

SUM INSURED (Rs.) 6600.00 PREMIUM (Rs.) 660 PREMIUM % 10%

Note: Payout of Deficit rainfall and Excess rainfall will be calculated on "either or basis" the cumulative payout of respective phases will be compared and which ever is more will be considered

UP - TermsheetCROP PADDY District Mathura RISK COVERED - Deficit RainfallIndex Aggregate Rainfall of Respective Phases below Trigger Value 1-Jul-13 16-Jul-13 1-Aug-13 16-Aug-13 1-Sep-13 16-Sep-13 15-Jul-13 31-Jul-13 15-Aug-13 31-Aug-13 16-Sep-13 30-Sep-13 Trigger 1 (mm) 80 100 90 80 40 25 Trigger 2 (mm) 20 30 20 20 10 5 Exit (mm) 0 0 0 0 0 0 Payout Rate 1 Rs/mm 5.25 10.5 10.5 10.5 10.5 5.25 Payout Rate 2 Rs/mm 71.75 150.5 313.25 406.05 843.6 679 May Payout 1750 5250 7000 8751 8751 3500 Total Max Payout 35002 RISK COVERED - Excess Rainfall(2 days consecutive rainfall of respective phase(Multiple pay out) 1-Jul-13 16-Jul-13 1-Aug-13 16-Aug-13 1-Sep-13 16-Sep-13 1-Oct-13 15-Jul-13 31-Jul-13 15-Aug-13 31-Aug-13 16-Sep-13 30-Sep-13 15-Oct-13Trigger 1 (mm) 120 150 140 140 100 80 50Trigger 2 (mm) 200 230 220 220 180 160 130Exit (mm) 300 330 320 320 280 260 230Payout Rate 1 Rs/mm 4 8 8 8 10 10 6Payout Rate 2 Rs/mm 9.92 15.47 15.47 15.47 27 27 21.45May Payout 1312 2187 2187 2187 3500 3500 2625Total Max Payout 17498 Total Sum Insured (Rs.) 52500 Total Premium (Rs.) 5250 Farmer's share (Rs.) 1312.5

Bihar Termsheet

Claim Settlement Mechanism

• Over 2500 weather stations installed to settle weather insurance claims– Stations installed by approved third party

administrators• AWS prototypes certified by the local Met department• State/provincial govts decide the no. of stations to be

installed• Insurance Companies pay the data fees• Satlleite data being studied, fails to capture local variations

• Crop cutting experiments to be independently audited by third party service providers

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