Making Insurance Markets Work for Farmers in India (November 2010)

8/6/2019 Making Insurance Markets Work for Farmers in India (November 2010)

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ABOUT THE AUTHORS

OLIVIER MAHUL([email protected])is the Co-task Team Leader andProgram Coordinator in theFinance and Private-SectorDevelopment Global CapitalMarkets Non-Banking Unit. Hehas expertise in agriculturalinsurance and disaster riskfnancing.

NIRAJ VERMA([email protected])is the Co-task Team Leader and

Senior Financial SectorSpecialist in the South AsiaRegion Finance and Private-Sector Development Unit. Hisexpertise is in banking andaccess to fnance.

APPROVING MANAGERIvan Rossignol, Sector Managero the South Asia Finance andPrivate-Sector DevelopmentUnit.

Loic Chiquier, Sector Managero the Finance and Private-Sector Development GlobalCapital Markets Non-BankingUnit.

Making Insurance Markets Work or Farmersin India

Indias crop insurance program is the worlds largest with 25 million farmersinsured. Yet 85 million farmer households are not covered. Issues in design,

particularly related to delays in claims settlements, explain the low coverage.To address these problems, the World Bank provided actuarial inputs,engaged in policy dialogue, and facilitated the launch of an innovative cropinsurance program that would improve equity, risk mitigation, and claims

settlement for farmers; provide tools for budget management and agricultural policy for government; and open up the market for public- and

private-sector insurers and reinsurers. Initially, the program will be availableto an estimated 8 to 10 million farmers, of whom 3 million are expected to

participate in the rst year with a total sum insured in excess of $1 billion.Over time, this project could be scaled up to be available to Indias 110million farmers. This SmartLesson describes lessons learned in developingand implementing the crop insurance program.

Background

The need. With a high degree of dependenceon rain-fed cultivation, India needs a well-developed and widely used agricultureinsurance program. For more than 110 millionfarmer households (of whom 80 percent aresmall and marginal farmers operating lessthan two hectares), access to risk mitigationfor crop production is critical. Otherwise, theyrun the risk of crop failures, which in turn,leads to an inability to service debts. Becausesuccessive crop cycles follow seamlessly fromone to the next, delinquency on account ofone crop failure means being ruled out of theformal banking system, leading to dependenceon high-cost informal sector credit and apotential debt trap. Crop insurance also helpsenhance the viability of agriculture lendingthrough risk mitigation and hence is vital forbanks.

The response so ar. The government of India(GOI) has historically focused on crop insuranceas a planned mechanism to mitigate the risksof natural perils on farm production. TheNational Agriculture Insurance Scheme (NAIS),implemented by the public crop insurer, the

Agriculture Insurance Company of India (AICI),is the main crop insurance program in thecountry and has been supplemented morerecently by the Weather-Based Crop InsuranceScheme (WBCIS).

The broad structure of NAIS is technicallysound and appropriate in the context of India.NAIS is based on an indexed approach knownas the area yield-based approach, where theindex used is the crop yield of a de ned areacalled an insurance unit (IU, e.g., anadministrative block). The actual yield of theinsured crop, measured by crop-cuttingexperiments in the IU, is compared to historicalyields. If the former is lower than the latter, allinsured farmers in the IU are eligible for thesame rate of indemnity payout. Individualcrop insurance would have been virtuallyimpossible, given the large number of verysmall landholdings. Further, using the areayield-based approach has other merits. Mostimportantly, it mitigates moral hazards andadverse selection.

The problem. NAIS is funded by post-disastergovernment contributions, entailing an open-ended and highly variable scal exposure for

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the government. Being subsidized, the annual claim/ farmers premium ratio is higher than 100 percent. At theend of the crop season, aggregate claims exceeding thefarmers premium, are funded 50-50 by the state andcentral governments. Indias post-disaster fundingarrangement, which, in turn, was necessitated on accountof a lack of an actuarially sound premium ratingmethodology without which estimating payouts is notfeasible, is not optimum for budget management for theGOI and delays claims settlement, leading to farmersdistress and exposing them to a vicious debt cycle. Thissituation explains NAISs low coverage (20 percent) and thatof banks lending to farmers (45 percent).

The solution. The GOI asked the World Bank to improve thecrop insurance program through an actuarially sound ratingmethodology that would improve the design of NAIS andreduce delays in claims settlement. The Bank was asked topropose design and ratemaking of new weather indexinsurance products under the WBCIS, perform a riskassessment of AICIs insurance portfolio, and suggest cost-effective risk nancing solutions (including reinsurance).The project, conducted in three successive phases,culminated in 2010 and entailed working closely with theclient and national and international experts. The Bank alsoprovided capacity building in the form of quarterly visits bythe Banks team (including a certi ed actuary) and monthlyteleconferences.

This work started with funding from the Swiss Developmentand Cooperation Agency (Phase 1, 2005) to engage adialogue with the GOI on agricultural insurance. DuringPhase 2, 20052007, the FIRST Initiative provided technicaland nancial assistance for the development of anactuarially sound product design and ratemakingmethodology for the NAIS and the WBCIS. Under Phase 3(20082010) of the nonlending technical assistance (NLTA),funded by the Global Facility for Disaster Reduction andRecovery, the actuarial methodology developed underPhase 2 was made operational through the development ofprototype actuarial software and intensive technicalcapacity building. In addition, these actuarial and riskassessment tools were used as part of a policy dialogue onthe scal impact of agricultural insurance.

The NLTA Project produced the following key outputs andmilestones:

a detailed review of NAIS, including its underwritingand ratemaking methodology.

development of a best practice standard actuarially sound ratemaking procedure (as a public good) usingan experience-based approach for area-yield insurance.This became the foundation for a move to an ex-ante,market-based crop insurance program, as the actuarial prices helped assess farmer, state, and centralgovernment contributions to premiums up front.

development of commercial weather-based cropinsurance products, which led to an increase in the AICIweather-based crop insurance portfolio to almost 1million farmers and a total annual premium volume inexcess of $50 million.

detailed inputs into the design of the innovativemodi ed NAIS (mNAIS) for India (see Box 1).

a buildup of AICIs capacity to transition NAIS to amarket-based approach.

a policy dialogue, in parallel with the Ministry ofFinance, the Ministry of Agriculture, and the PlanningCommission, about the scal impact of the modi edNAIS for the GOI as well as the welfare implications ofthe modi ed scheme

a decision to launch an mNAIS pilot in 50 districts forthree seasons, starting in Rabi in the winter of 2010.

prototype actuarial software design and pricing of morethan 200 insurance products, as well as advice on the useof mobile technology for improving crop-cutting dataquality and timeliness.

In September 2010, the GOI approved the mNAIS, re ectingmost of the Banks suggestions, moving from a social cropinsurance scheme to a market-based crop insurance programinvolving the private insurance and reinsurance industry.The implications of this project for the performance and

Box 1. Main Features of mNAIS

Actuarial regime: The mNAIS scheme operates on an actuarial regime in which the governments nancial liability would be predomi-nantly in the form of premium subsidies given to AICI and funded ex-ante, thereby reducing the contingent and uncertain ex-post scal exposurecurrently faced by the government under NAIS, and reducing delays in claims settlement. Up- ront premium subsidies: AICI receives premiums (farmer collections + premium subsidies from the government) and is responsiblefor managing the liability of the mNAIS through risk transfer to private reinsurance markets and risk retention through its reserves and is ableto operate on a sustainable basis. On-account partial payment: The mNAIS product continues to be based on an area yield-based approach, with a provision for an earlypart payment to farmers (in season) based on weather indices. Small IUs: Crop-cutting experiments conducted to assess crop yield estimates are lowered from the block level to the village level to reducebasis risk (i.e., the mismatch between the actual individual crop yield losses and the insurance indemnity). Cuto dates. Adverse selection is reduced through the enforcement of early purchase deadlines in advance of the crop season. Additional benefts. Additional bene ts are offered for prevention of sowing, replanting, post-harvest losses, and localized risk such ashail losses or landslides.


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sustainability of the mNAIS are monumental: Althoughinitially this product could be available to 8 to 10 millionfarmers, over time it could be expanded to Indias 110million farmer households with improved crop insuranceproducts and timely claims settlement (see Box 2 for keybene ts of mNAIS). The modi ed scheme crowds in theprivate insurance sector by allowing domestic insurancecompanies to offer mNAIS and by attracting internationalreinsurance capacity. Finally, the GOI will be better equippedto manage its scal exposure to natural disasters, whileinsurance companies will now bear risks and compete tooffer products and services to farmers.

Lessons Learned

1) Make sure that any state-of-the-art tools aredeveloped in close collaboration with the client, and be

prepared to deploy second-best technical solutionswhen necessary to re ect on-the-ground realities and

political and economic considerations.

Drawing on international best practice and in-countryexperience, the rating methodology improves pricing ofcatastrophic losses and allows decomposition betweencatastrophic and noncatastrophic losses, which helps attractinternational reinsurance capacity. The rating methodology

ensured the nancial sustainability of the program and itsrelevance to the country context. An open approach helpedclose collaboration with the client, leading to drawing ontheir country and domain knowledge to a signi cantextent, a process which also enabled the Bank team to learnfrom the clients experience and knowledge.

Adaptations were required in order to make the ratingmethodology practical. For example, while risk differentiationis desirable from an actuarial viewpoint, applying it to each IU(left side, Figure 1) would have been dif cult because ofpolitical and administrative constraints. A second-bestapproach was deployed, using district pricing (right side,Figure 1) and a strategy to keep the nominal price constantbut vary the coverage levels (insurance deductibles).

2) Design technical tools that can pave the way for policy dialogue.

The actuarial tool by itself was the de ned output soughtby the client. These actuarial tools were used as the basis fora shift from ex-post to ex-ante funding. They were also usedto demonstrate ef ciency and the political and economicgains possible through faster claims settlements. The toolstherefore helped translate technical work into policydialogue. The result was the launch of a new programpotentially bene ting Indias 110 million farmers in thecoming years.

Figure 1. Pure Premium Rate at 90% Coverage Level, Rice Cropin Province A

Figure 2. NAIS Premium Income and Claims by State

Note: Rs 1 lakh is approx. $2,500.

Box 2: Key Bene ts from mNAIS

Actuarial rating enables risk-based pricing and ex-ante estimation of subsidy (better budget management).Risk-based pricing helps differentiate risks and improve equity between farmers (Figure 1 shows highly varied risk pro les within a state al-though all farmers were earlier paying the same premium under NAIS). Risk-based pricing can also be used for agriculture policy signaling. Foexample, in the case of a crop with a very high premium rate, the mNAIS could indicate that it should not be grown in a given area, and thiscould feed into agriculture extension policy. Ex-ante subsidy determination enables up-front government and farmer contributions toward premiums, thereby passing residual risks to the

insurers (market approach) and enabling fast claim settlements. Combining weather-indexed insurance (that allows for quick payments and enables interim payments within a crop season) with area yieldinsurance (that allows for payouts with closer correlation to yield losses) makes the best use of both indices. Improving the underwriting terms and conditions of the crop insurance policy, such as purchase deadlines and additional bene ts, makes theproduct more sustainable. Increasing competition and expanding the role of the private sector in crop insurance contribute to the promotion of effective public-privatepartnerships in agricultural insurance.


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Further, actuarially sound premiums signaledthe true cost of growing a given crop in agiven district and informed decision makersabout the viability of some crops in someregions and the social cost of maintainingthem. The actuarial tools were also used toinform policymakers about the scal impactof public premium subsidy programs, assesstargeting (coverage of crops and small andmarginal farmers versus others), and analyzethe associated wealth transfers between thecentral government and the states (Figures 2and 3).

3) Invest in extensive institutional capacity building and technical inputs for both theimplementing agency and policymakers.

Agricultural insurance is a highly specializedline of business that requires intensiveinstitutional capacity building. Major effortswere invested to ensure that the proposedtechnical recommendations would be fullyunderstood and implemented. Anchor andregional staff, with the assistance of aninternational certi ed actuary, providedintensive training to AICI technical staff throughtechnical documents, monthly teleconferences,and quarterly on-site visits.

4) Combine traditional and innovative cropinsurance.

Although much of the developmentliterature and debate in India and elsewherecenter on traditional versus new generation(weather-based) insurance, the team hereused technical grounds to demonstrate thebene ts of combining the two approaches,based on their respective comparativeadvantages. Weather-based indices are usedfor on-account partial payment of claims incase of adverse mid-season conditions, whilearea yield indices are used for nal paymentof claims.

DISCLAIMERIFC SmartLessons is an awardsprogram to share lessons learnedin development-oriented advisoryservices and investmentoperations. The fndings,interpretations, and conclusionsexpressed in this paper are thoseo the author(s) and do notnecessarily re ect the views o IFCor its partner organizations, theExecutive Directors o The WorldBank or the governments theyrepresent. IFC does not assumeany responsibility or thecompleteness or accuracy o thein ormation contained in thisdocument. Please see the termsand conditions at www.i c.org/smartlessons or contact theprogram at smartlessons@i c.org.

Conclusion

The shift from a social crop insuranceprogram with ad-hoc funding from theGOI to a market-based crop insuranceprogram where the product design andpremium rates are actuarially soundmakes the Indian crop insuranceprogram attractive for private insuranceand reinsurance companies. Twodomestic private insurers alreadyagreed with some states to offer mNAISin Rabi in 2010. The public insurer AICI iscurrently looking for internationalreinsurance capacity for its mNAISinsurance portfolio.

The piloting of mNAIS is under way in 50districts (around a tenth of India). This is amajor step forward and can help improve riskmitigation for farmers, bene t lenders tofarmers, improve budget management, anddevelop private insurance markets. However,key challenges remain, including improvingyield estimation, promotion of the product,and streamlining of the budget processes. TheBank team is in discussions regarding follow-up support for institutional capacity building,implementation assistance to increaseoutreach, and further ne-tuning of theproduct to support development of the cropinsurance market.

Figure 3. NAIS Loss Ratio for Major Crops, 2000-07

Documents

Making Insurance Markets Work for Farmers in India (November 2010)