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Baac weather index insurance.ppt(special)

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  • I really appreciate the host for inviting BAAC to join this forum. What I’m speaking today derived from BAAC’s experience on Agricultural Weather Index Insurance.
  • This presentation comprises 5 elements About BAAC To get to know why BAAC is involved in risk management. Why risk management? The need to perform risk management How to manage risk? Or how can we mitigate risk? Weather index Insurance Next step , what shall be done next?
  • BAAC’s vision focuses on the importance of the uplift of small scale farmers’ quality of life.
  • BAAC has provided financial assistance to 6.1 million farmers, or 98 % of total farm households through its extensive branch network, covering every district across the country.
  • At the end of fiscal year 2009 , the loan outstanding was USD 15.78 billion, of which 90% was loans extended to individual farmers .
  • Deposits from general public is the main source of fund, accounted for 84% of total operating fund. That is why we need to manage risk in agriculture.
  • There are 7 key factors in management of risk in agricultural sector. Importance of agriculture Vulnerability to hydro-meteorological risks Burden on public resources Good weather data infrastructure Strong interest from stakeholders Growing insurance sector Strong agricultural bank
  • There are 2 approaches , traditional agricultural reinsurance and weather index insurance .
  • In response to this challenges, effective and cost-effective crop insurance programs have been designed. One of those is weather index insurance.
  • What does weather index insurance in Thailand look like?
  • A cotton insurance was pilot-tested in Thailand in 1977. Several attempt has been made to run such insurance. However, it was stuck by earlier mentioned problems. In 2006, the weather index insurance was introduced.
  • We purse here a model of “ Bank-intermediated weather insurance contracts to farmers” Farmers expose to weather risks which result in difficulty in paying back their loans. They want to have insurance, but lack of access to insurance companies which are mostly urban-based. In this situation, it is more efficient to have an institution perform the role of a risk aggregator. This could be performed by Ag. Banks or any organization with farmer outreach, for , Village Banks and Cooperatives. The Bank could intermediate the contracts to the farmers. This could also be linked to loans.
  • We currently have 2 models, World Bank model and JBIC model.
  • Let me introduce you World Bank model first. These are samples of rain gauges which are very important to weather index insurance operation.
  • This model has been implemented in India and many countries in Africa.
  • This picture displays World Bank’s drought insurance , covering 3 periods of maize production .
  • BAAC pilot-tested weather index insurance in 1 district in 2006. No insurance fee was collected.
  • In 2007, index insurance was fully implemented in the pilot –testing district with participation of 35 farmers and fee collection of USD 2,590.
  • In 2008, the project was expanded, covering 8 districts in 5 provinces
  • In 2009, weather index insurance project was scaled up to 15 districts in 5 provinces.
  • In 2010, the project is being implemented in 7 provinces with over 3,000 farmer participants.
  • Later, JBIC proposed a different model from that of World Bank.
  • This model was implemented by Sompo Insurance Company registered in Thailand
  • The significant difference is cumulative rainfall at the end of harvest season used in the project. Insurance fee is 4.6 % of loan principle.
  • JBIC drought insurance for rice production model was pilot-tested in Khon Kaen in 2009. There were 276 farmers participating in this project. No insurance fee was collected.
  • Consequently, in 2009, JBIC model project was implemented with participation of 1,158 farmers. Participating farmers were required to pay insurance fee.
  • Both models tend to grow in terms of number of participating farmers and coverage area as well as fees collected under these projects
  • Transcript

    • 1.
      • Mr. Kamolpant Asaves
      • Executive Vice President of BAAC
      18 November 2010 Agricultural Weather Index Insurance in Thailand Bank for Agriculture and Agricultural Cooperatives (BAAC)
    • 2. V. Next Step IV. Weather Index Insurance III. How to Manage Risk? II. Why Risk Management? I. About BAAC Agricultural Weather Index Insurance in Thailand
    • 3. I. About BAAC Agricultural Weather Index Insurance in Thailand
    • 4. BAAC Vision 2010
      • “ To be secured rural development bank
      • with modern managerial technology
      • focusing on the uplift of small scale
      • farmers’ quality of life”
      About BAAC Rural Development Sustain Modern Better Living
    • 5. BAAC Delivery Structure HEAD OFFICE DEPARTMENTS/DIVISIONS PROVINCIAL OFFICES (75) DISTRICT BRANCHES (977) FIELD OFFICES (957) CLIENTS (6,101,206) Bank Management and Policy Branch Administration and Support Supervision of Activities Credit Delivery to Clients Individual Clients (Joint Liability Groups) Agricultural Cooperatives Farmers’ Associations BUSINESS DEVELOPMENT OFFICERS contact with clients About BAAC
    • 6. Credit Services (as of the end of March 2010) Total 15,776 million (Unit: USD) About BAAC
    • 7. Operating Fund (as of the end of March 2010) Total 23,905 million (Unit: USD) About BAAC
    • 8. II. Why Risk Management? Agricultural Weather Index Insurance in Thailand
    • 9. Why Risk Management for Agricultural Sector? Importance of Agriculture Vulnerability to Hydro-meteorological Risks Burden on Public Resources Growing Insurance Sector Good Weather Data Infrastructure Strong Interest from Stakeholders Why Risk Management? Strong Agricultural Bank 1 2 6 3 7 5 4
    • 10. III. How to Manage Risk? Agricultural Weather Index Insurance in Thailand
    • 11. Crop Insurance Weather Index Insurance How to Manage Risk? How to Manage Risk? Production Risk
    • 12.
      • Parametric Insurance
        • - Weather-based
        • - Area-yield
        • - Satellite imagery (NDVI)
        • - Other indices
      • Traditional Agricultural Reinsurance
        • - Named perils
        • - Multi-Peril Crop Insurance (MPCI)
      How to Manage Risk? Tools
    • 13.
        • Moral hazard, adverse selection,
        • high monitoring and administrative cost
      How to Manage Risk? Traditional Crop Insurance
    • 14. How to Manage Risk? Design an alternative, efficient and cost-effective crop failure insurance program Challenge that can be easily reinsured and distributed to individual farmers: small, medium and large Weather-based
    • 15. IV. Weather Index Insurance Agricultural Weather Index Insurance in Thailand
    • 16. Project Crop Insurance : Cotton (1977) Weather Index Insurance (2006-2010) Weather Index Insurance in Thailand
    • 17. Project Model of Weather Index Insurance
      • Bank-intermediated weather insurance contracts to farmers
      Reinsurance Treaty Thailand International Weather Insurance Policy Contractual Relationship (risk transfer, services, operations etc.) Weather Index Insurance in Thailand Insurance Company/ Syndicate Global Reinsurance Companies Farmers BAAC
    • 18. Project Model Weather Index Insurance in Thailand Model of the World Bank Model of the Japan Bank for International Cooperation (JBIC)
    • 19. India Rain Measurement Tool Model of the World Bank Manual Rain Gauge Automatic Rain Gauge Weather Index Insurance in Thailand
    • 20.
      • Market-based Risk Transfer Products
      • Weather index-based insurance
      • Price risk management contracts
      • Knowledge Transfer and Education
      • Technical assistance
      • Publications and training workshops
      • New Applications
      • Disaster risk financing
      • Extension to new hazards
      • Existing Transaction
      • India, Ethiopia,
      • Malawi, Ukraine,
      • Mongolia …
      Weather Index Insurance in Thailand Commodity Risk Management of the World Bank
      • Access to risk capital
      • Access to global reinsurance markets
    • 21. Maize Rainfall Index *Maize yields are particularly sensitive to rainfall during the tasseling stage and the yield formation stage – rainfall during the latter phase determines the size of the maize grain Weights and diagram taken from the FAO’s maize water requirement report* x Cumulative Rainfall in each decade = Maize Rainfall Index Weather Index Insurance in Thailand
    • 22. July 2006 Maize Production 110 Farmers 1,970 Acres of maize enrolled The Radius of 25 km. Measured from the Suwan Maize Research Center Station Weather Index Insurance Nakorn Ratchasima Province, Pak Chong District GIA TMD DOI RID Department of Insurance (DOI) General Insurance Association (GIA) Thai Meteorological Department (TMD) Royal Irrigation Department (RID) Weather Index Insurance in Thailand Testing Project in 2006
    • 23. Period 3 Period 2 Period 1 Premium rates Seedling Emergence to Knee High (Days 30) Knee Height (Days 21) Physiological Maturity (Days 30) USD 96/Acre USD 127/Acre USD 134/Acre BAAC’s Pakchong Branch Station Suwan Maize Research Center Station 35 Farmers 380 Acres
      • Premium: USD 2,590
      • Sum insured: USD 41,620
      July 2007 Risk cover : Drought Insured Crop: Maize Rain station Rain station Nakhon Ratchasima Province Pilot Project in 2007 USD 9/Acre USD 9/Acre Weather Index Insurance in Thailand
    • 24. 2,860 Acres 388 Farmers Sowing (30 Days) Growth (20 Days) Flowering and Grain Filling (30 Days). USD 28/Acre USD 104/Acre Nakhon Ratchasima Lopburi Saraburi Nakhon Sawan Phetchabun 5 Provinces (8 Districts) Pilot Project in 2008 Weather Index Insurance in Thailand USD 10/Acre USD 6/Acre Period 3 Period 2 Period 1 Premium: USD 23,300 Indemnity: USD 3,520 (15% of Premium) Premium rates
    • 25. 5,320 Acres 817 Farmers Sowing (30 Days) Growth (20 Days) Flowering and Grain Filling (30 Days). USD 28/Acre USD 104/Acre Nakhon Ratchasima Lopburi Saraburi Nakhon Sawan Phetchabun 5 Provinces (15 Districts) Pilot Project in 2009 Weather Index Insurance in Thailand USD 8/Acre Period 3 Period 2 Period 1 Premium rates Premium: USD 42,040 Indemnity: USD 11,160 (27% of Premium)
    • 26. 24,275 Acres 3,194 Farmers 7 Provinces (as of the end of September 2010) Nakhon Ratchasima Lopburi Saraburi Nakhon Sawan Phetchabun Pitsanulok Nan Pilot Project in 2010 USD 8/Acre Sowing (30 Days) Growth (20 Days) Flowering and Grain Filling (30 Days). USD 28/Acre USD 104/Acre Weather Index Insurance in Thailand Premium: USD 202,290 Indemnity: USD 143,300 (70% of Premium) Premium rates Period 3 Period 2 Period 1
    • 27. Model of the Japan Bank for International Cooperation (JBIC) Weather Index Insurance in Thailand
    • 28. Overview Project Thailand Japan Sompo Japan Group Insurance Contracts Thai Meteorological Department (TMD ) Coordination MOU Technical Advice Technical Advice (Insurer) (Policy Holder) (Insured) Weather Index Insurance in Thailand National Institute for Agro-Environmental Sciences (NIAES) BAAC Sompo Japan Sompo Japan Risk Management JBIC JBIC Thailand Sompo Japan Thailand
    • 29. Upper Threshold Lower Threshold Premium rate: 4.64% of principle Drought : Indemnity 15 % of the insured loan principal Severe Drought : Indemnity 40 % of the insured loan principal Non-Drought (No Indemnity) Model of JBIC Weather Index Insurance in Thailand Cumulative Rainfall (mm.) in July – September (3 months)
    • 30. July-September 2009 Rice Production 276 Farmers, 5 Districts, 2,270 Acres Weather Station at District Weather Index Insurance Khon Kaen Province SJIT TMD JBIC OIC Japan Bank for International Cooperation (JBIC) Sompo Japan Insurance (Thailand) Co., Ltd. (SJIT) Thai Meteorological Department (TMD) Office of Insurance Committee (OIC) Cumulative Rainfall (mm.) Testing Project in 2009 Weather Index Insurance in Thailand Premium: USD 14,360
    • 31. July-September 2010 Rice Production 1,158 Farmers, 26 Districts, 3,180 Acres Weather Station at District Weather Index Insurance Khon Kaen Province SJIT TMD JBIC OIC Japan Bank for International Cooperation (JBIC) Sompo Japan Insurance (Thailand) Co., Ltd. (SJIT) Thai Meteorological Department (TMD) Office of Insurance Committee (OIC) Cumulative Rainfall (mm.) (as of the end of September 2010) Testing Project in 2010 Weather Index Insurance in Thailand Premium: USD 24,700 Indemnity: USD 3,950 (16% of Premium) Good Result Return: USD 7,620 (31% of Premium)
    • 32. Project Summary 2007 2008 2009 2010 (August) Year Farmers Acre Premium (USD) Trend 35 2,590 380 42,040 23,300 388 2,860 817 5,320 Premium (USD): 14,360 -----> 24,700 Weather Index Insurance in Thailand 3,194 24,275 202,290 Maize (from 5 to 7 Provinces) Rice ( 1 Province: from 5 to 26 Districts) Farmers: 276 -----> 1,158
    • 33.
      • Non-complicated Model
      Important Lessons Collaboration of Relevant Parties Perception and Understanding of Farmers Direct Benefit to Farmers Confidence of Measurement Weather Index Insurance in Thailand
    • 34. V. Next Step Agricultural Weather Index Insurance in Thailand
    • 35.
      • Extend to Other Crops
      Important Lessons
      • Study the Flood Model
      • Model for Other Countries
      Next Step
    • 36. THANK YOU Bank for Agriculture and Agricultural Cooperatives (BAAC)

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