Potential use of historical reanalysis by agricultural re/insurance industry

1. Potential use of historical reanalysis by agricultural re/insurance industry Olena Sosenko Australia April, 2009

2. Content • Global agriculture • Agriculture and climate change • Interest of re/insurance industry in climate/weather data • What kind of data is required and how it is used • Data period, data consumers • Product solutions for ag and ag insurance industries • Special solutions for emerging markets

3. Global agriculture • 1.7 billion more mouth to feed by 2030 • Food is driver for revolutions and wars • 70% of the world water is used for agriculture • 90% of risks are weather/climate related • Production variability, reducing arable land, drought, desertification, flooding, soil salinity and erosion

4. Rainfall and yield variability Australia

5. Potential impacts of climate change on crop production Source: Climate change, impacts and adaptation. Canadian website.

6. Climate change points leading to insurance opportunities • Increasing of yield variability and production risk • Increasing of water stress problems: drought and flooding • Increasing of agri risk management importance • Increasing of demand for new products/covers • Innovative types of insurance relating to climate and climate change • Index insurance products (weather index, yield index) • NDVI (satellite) based insurance

7. Interest of re/insurance industry in weather/climate data

8. What kind of data the ag insurance industry requires • Digital • Annual/ seasonal/ per month/ per event • Long term records only at the stage of insurance program development • Might need the same data yearly for product implementation • Easy accessible, reasonable price • High spatial resolution (per administrative unit, agroecological zone) • If modelled (or in case of forecast) – high preciseness

9. How ag re/insurance industry uses the data • Price the pure cost of risk (frequency x severity) = net rate. Burning analysis • Create catastrophic models (return period of cat events) • Define the covered trigger (index products) • Confirm loss occurrence, trigger hit • Calculate the indemnity (index product)

10. Choice of data period

11. Who are the data consumers in case of ag risk management • Re/insurance companies • Underwriting agencies • Loss adjustment companies • Consulting companies • Government working groups • Ag growers • Marketing companies (AWB) • World Bank, UN: agro risk management projects

12. Example of weather/climate indices used for ag insurance

13. Some demanded data enhancements or innovations for re/insurance needs • Risk mapping (hail, storm pathways) • Modelling and prediction of winter risk scenarios in Northern hemisphere • Drought modelling and prediction • Climate extreme trends • Improvement of data spatial homogeneity

14. Product solutions for ag and ag insurance industries Climate models / weather forecast Queensland government, Department of Primary Industries

15. Product solutions for ag and ag insurance industries Crop models

16. Application for re/insurance industry

17. Use of crop models for insurance programs

18. Special solutions for emerging markets India Source: presentation of the World Bank

19. Special solutions for emerging markets • India • Rainfall Index insurance product: since 2003, ICICI Lombard + the World Bank • Crop yield-based scheme in frame of National Agricultural Insurance Scheme implemented by Agricultural Insurance Company of India • Mongolia:Index-based livestock insurance, protection from dzud. • Peru: ENSO-based flood insurance for ag income related institutions • Mexico • Used weather derivative to reinsure the crop insurance program • Rainfall insurance contracts in conjunction with water rights

20. Thanks for your attention!