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IFPRI-New technologies for better Insurance: Picture Based Crop Insurance-Berber Kramer

  1. New technologies for better insurance: Picture Based Crop Insurance Berber Kramer (B.Kramer@cgiar.org) IFPRI Research team: Miguel Robles (M.Robles@cgiar.org) Francisco Ceballos (F.Ceballos@cgiar.org) New Delhi, December 21 2016
  2. Why do farmers lack crop insurance? • Farmers too remote and too small for indemnity insurance • Administrative costs • Costs of loss verification • Monitoring of cheating / Moral hazard • Index insurance • Basis risk • Beyond the control of the farmer • Technological innovations: • Satellites: Difficult to understand, cloud cover • Drones: Better resolution but high operational cost • Generally: High biodiversity and small scale • How to bundle the best of these worlds?
  3. Opportunity:Rise of Smartphones Source: Global Attitudes Spring 2015 & 2014, PEW Research Center In 2015, there were 220 million unique smartphone users in India
  4. Greenness index estimation Onlineserver GCC reference curve GCC curve Machine learning Low-cost loss assessment Farmers take pictures Additional information CCE A hybrid insurance approach
  5. Wecantestwaystolimitmoralhazard Remote sensing from above to detect anomalous behavior? Use nearby farmers as a benchmark? Pictures, data, sensors Experts /Agronomists - Weather stations - Satellite images… Agro-advise Use agro-advisories?
  6. Bundled with other services • Use pictures to provide agro-advisory services • This is a natural complementarity • PBI is already collecting rich field data • Data can be analyzed by experts to provide advise • Incentive to report truthfully and not cheat the system Pictures, data, sensors Experts /Agronomists - Weather stations - Satellite images… Agro-advise
  7. What do we need to get there? • Pictures and data for machine learning • Not only pictures of damage: Algorithms will need both damaged and non-damaged pictures • Not only data on yields: Farmers’ perceived damage, causes of damage, practices, etc. • High-frequency at first in order to estimate optimal frequency and need for standardization • Farmers’ interest in such products • Not only their willingness to pay • Also impacts on behavior: investments and cheating
  8. IFPRI’s Picture Based Crop Insurance • States:Punjab&Haryana • 6districts • 50villages • 750farmers • Wheatcrop(winter/rabi)
  9. Wheat Cam Firststeptowardsnewcropinsuranceapproach • Collectpicturesanddatawithhighfrequency • Includeperceived damageandcauseofdamage • Practices andinputuse(seed andsoiltype,fertilizer,etc.) • Yieldsattheendoftheseason (cropcut) • Assesspracticalfeasibility • Canfarmers usetheappandsubmitpictures?Howoften? • Canwepredictdamage(orevenyield)onthebasisofthepictures? • Assessfarmers’interestin,andresponseto,suchproducts
  10. Smartphone app • Android app • User friendly • Facilitates taking pictures at exactly same location • Relies on GPS coordinates • Short survey after taking picture • Important for later analysis • Input use and practices • Currently standardized procedures with reference poles and auxiliary poles Wheat Cam
  11. Auxiliary Pole Reference Pole
  12. Aplicación Android
  13. Addingsites…
  14. Capturing initial picture…
  15. Choosesite Capturing repeat pictures…
  16. Picturecanbe takenonlybetween 10AMand2PM… Capturing repeat pictures…
  17. Initialpictureshownasghost imageinthebackground… Capturing repeat pictures…
  18. Capturing repeat pictures…
  19. Afterwards,thefarmer answersafewquestions… (dataformachinelearning)
  20. N = 1317
  21. As of now, 290 (22.02%) pictures where farmer selected ‘Yes’. - 3 fully damaged - 33 partially damaged - 257 slightly damaged No visible damage in 11.7% of these pictures.
  22. Take-up of the technology
  23. Example of good pictures
  24. Example of good pictures
  25. Example of good pictures
  26. Example of bad pictures
  27. Example of bad pictures
  28. Example of bad pictures
  29. Committee of experts Reviews pictures + additional information Onlineserver Loss assessment (or field visit) Farmers take regular pictures This year Machine learning
  30. Advantages and Disadvantages If smartphone pictures accurately capture damage, then picture-based crop insurance can contribute: Lower basis risk (going back to indemnity product) Easy to understand, easy to relate to (farmer is at the center) Complements weather index-based products Leverages increasing use of smart-phones Feasible for the insurance companies Main risk: Potential moral hazard To what extent is there moral hazard? (this year) How to design the product to limit potential hazard?
  31. THANK YOU Questions: B.Kramer@cgiar.org
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