Index based insurance
 schemes: Way ahead
 Mangesh Patankar, CIRM
Challenges in the current crop
        insurance schemes
• Area yield –
  – Lack of re-insurance
     • Unsustainable loss...
Composite
                                          products
                 Innovations
                                ...
Composite products:
• Combine area yield with weather index
  – E.g Combine weather index with vegetation
    index from r...
Products in data constrained
            geographies
• RFE products: Spatial rather than point based
  measurement




• V...
Modular products
• Weather tickets - Based on the self
  assessment of risks: IFPRI and Nyala
  Insurance Company
        ...
Comparative analysis
Area Yield
Costs incurred in administration




                                                                 Weather i...
Weather-NDVI
                                            composite
                             RFE                     ND...
RFE


                                      Weather-NDVI
                                      composite

                ...
Process innovations
• Bundling weather insurance with
  – Agri–inputs: WRMS-ICICI Lombard product
    for Pioneer seeds
  ...
THANK YOU…
NDVI
NDVI – Our experience
• Pilot product for 2 districts: Surguja
  (Chhattisgarh) and Nizamabad (AP)
• Research on acceptabi...
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Index based insurance schemes - Way ahead!

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Presented at UNDP-CIRM National Microinsurance Conference, New Delhi in December 2009. Mangesh was a panelist for the panel named "Issues and innovation: Crop insurance". The other panelists included Harini Kannan of Swiss Re, Gunaranjan - a former employee of BASIX, Mr. K N Rao of Agriculture insurance company. The facilitator was Dr. Siddharth Sinha.

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Index based insurance schemes - Way ahead!

  1. 1. Index based insurance schemes: Way ahead Mangesh Patankar, CIRM
  2. 2. Challenges in the current crop insurance schemes • Area yield – – Lack of re-insurance • Unsustainable loss ratio • High administration costs • Settlement time (Manual claim estimation) • Weather index – – Basis risk: Particularly for rainfall products – Limited scale up opportunities: (Weather infrastructure and data issues) Need for subsidies
  3. 3. Composite products Innovations Alternate measuring • Lower basis risk Product • Data constrained geography Weather • Modular product tickets! Bundling •Indirect sale Process •Awareness Education modules
  4. 4. Composite products: • Combine area yield with weather index – E.g Combine weather index with vegetation index from remote sensing data: NDVI (Normalized difference vegetative index) • Portfolio insurance products – E.g. ILRI product in North Kenya • Providing agro-advisory services with insurance – E.g. BASIX, WRMS
  5. 5. Products in data constrained geographies • RFE products: Spatial rather than point based measurement • Very high transparency of the data • Low accuracy – thus high basis risk • E.g. Ethiopian project involving WB, WFP and FAO for LEAP (Livelihoods – Early Assessment and Protection)
  6. 6. Modular products • Weather tickets - Based on the self assessment of risks: IFPRI and Nyala Insurance Company Sowing Sowing Flowering Harvesting Flowering Individual Weather Tickets Harvesting
  7. 7. Comparative analysis
  8. 8. Area Yield Costs incurred in administration Weather index Weather-NDVI composite NDVI RFE Transparency in settlements
  9. 9. Weather-NDVI composite RFE NDVI Speed of settlements Weather index Area Yield Accuracy
  10. 10. RFE Weather-NDVI composite NDVI Scalability Area Yield Weather index Complexity of product
  11. 11. Process innovations • Bundling weather insurance with – Agri–inputs: WRMS-ICICI Lombard product for Pioneer seeds – Contract farming processes: Pepsico
  12. 12. THANK YOU…
  13. 13. NDVI
  14. 14. NDVI – Our experience • Pilot product for 2 districts: Surguja (Chhattisgarh) and Nizamabad (AP) • Research on acceptability and accuracy of the composite index product • Demand side findings: – Perception towards index – Client education – Expected accuracy • Supply side findings: – Data availability and time required for ground truthing – Reinsurance Back

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