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Laura Johnson
Insurance through RS – December 2013
This is why we use index insurance: a new kind of insurance that helps farmers cope with climate risks and does not require farm visits.
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Kilimo Salama approaches insurance as if we were farmers
Large scale farm: $1000 Premium - $50 Visit Costs + $950, insure
vs.
Small scale farm: $10 Premium - $50 Visit Costs - $40, can’t insure
One single bad season affects a farmer for years. During one drought season, smallholder farmers can loose their entire harvest and lack the money to buy quality farm inputs the next season.
Traditional agricultural insurance has not been able to protect them as it relies on farm visits to assess losses.
The Challenge
Overview
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Mandate: Develop and implement agricultural insurance products for smallholder farmers
Started in 2009 by Syngenta Foundation in Kenya with 185 maize farmers
Kilimo Salama serves as an insurance intermediary doing product development, contract pricing and monitoring, client interface
Insured (through local insurance company, reinsurer) over 150,000 smallholder farmers in 2013 in Kenya and Rwanda, soon to launch in Tanzania
Main product - drought insurance linked to agricultural credit by MFI used for fertilizer and improved seed
Weather Index
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Measurements done using weather stations and/or satellites, linked to agronomic formulas to model required rainfall
Pricing based on historical rainfall data – now through satellites
Our rule of thumb is ‘We don’t visit the farm’
Covers risk of Drought, Excess rain and/or Weather-related disease - all defined through a weather index
Initially used network of 100 SFSA automated weather stations (AWS)
No/unreliable historical daily rainfall data in expansion countries
Expensive to install/maintain
Investigating Remote Sensing:
Partner with Columbia University’s Earth Institute (IRI) since January 2012
Analyse correlation between AWS and Satellite Rainfall Estimates , selecting ARC2
Rainfall estimates based on reflected EM radiation and cloud temperatures
Need for Remote Sensing
Comparing Satellite Rainfall Estimations with AWS Data In Western Kenya
mileskm
100200
Slide from IRI
Extensive ground proofing and dry runs for new crops, in new geographies
Continuous improvement of indexes
Investigating new satellites and data sources
Strong correlation for drought after 1+ year of work
