agricultural index insurance initiative accelerating agricultural insurance in india – the case of...
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Agricultural Index Insurance Initiative
Accelerating Agricultural Insurance in India –the case of Kilimo Salama in Kenya
FICCI seminar, New Delhi, 5 February 2011Fritz Brugger, Syngenta Foundation for Sustainable Agriculture
Kilimo Salama – Overview
• Background
– Kenya
– Insurance situation
– Partners
• Challenges
– Distribution
– Literacy
– Affordability
• Success factors
– Role of technology
– Product design
– Added value services
– Private sector partnerships
Agriculture Insurance Situation in Kenya
Insurance setup differs from India in several aspects:
• Product availability:
– Multi-peril crop insurance: product is in the Market, available only for large scale farmers (500+ acres)
9.6 mn Kenyans involved in smallholder agriculture (FAO CountrySTAT (2008))
– Index insurance introduced in 2009, still in pilot stage
• Role of government:
– Government plays no active role in providing agricultural insurance:
– No subsidies available
– No mandatory insurance linked to credit
– Limited availability of historic weather data and AWS
• Access to agricultural finance
– Limited because of magnitude of risk
Kilimo Salama – Partners
• Syngenta Foundation for Sustainable Agriculture
– Is a not for profit organisation with the mandate to support smallholder famers by increasing productivity, improving access to markets, and mitigating farming risks.
– Syngenta Foundation has been established by Syngenta International AG, an agro chemical and seeds company that works in over 90 countries and has 26,000 employees.
• UAP Insurance Limited
– a leading Kenyan insurance and financial services company with a presence in Kenya, Uganda and Southern Sudan.
– In March 2009 UAP insurance started a pilot to offer insurance to small farmers in Laikipia district and is now looking to expand this.
• Safaricom
– Largest telecom operator in Kenya. Pioneered mobile payment service M-Pesa with currently 9.4 mn accounts.
Current status of pilot and project goals
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Insurance products are only sustainable if they can reach scale
We currently insure 12,000 farmers in 5 areas in Kenya
We aim to offer insurance to farmers in all agricultural areas in Kenya by 2012
This will require investment in: The weather station network from 30 300
A significant investment in financial education
Agroclimatic zones
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Challenges to index insurance growth in Kenya
Challenges Responses
Weather data historic and AWS
Setting up network
Distributionno branch network in rural areas
Use of new distribution channels
Transaction costhigh number of small policies
Use of technology
Affordabilityhigh premium due to high risk
Product designPartnershipsAdded value services
Financial literacylow insurance literacylow trust in insurance
TrainingAdded value services
Automated Weather stations
• Setting up AWS network
• Rainfall, wind, temperature, humidity, radiation, leaf wettness
• Remote monitoring of weather station operations
• Security and operations
• Preparing private company
• Coordination with Kenya Met Dept
Overcoming the Distribution bottleneck
• Agrovets: Closest allies of farmers: Farming advice, Loans, Business success
• 8’000+ agrovet shops across Kenya’s farming areas
– Small shops, Very busy around planting (up to 70% of sales in two month)
• Challenges
– Insurance is not their core product - but has a positive impact on their business.
– Insurance registration process must be fast and convenient
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Mobile Technology – Reducing Transaction Cost
Mobile Platform
Empower stockists
Policy managementPremium collectionClaims paymentTraining monitoring
Client communicationAdded value services
Kilimo Salama Mobile Application
Agrovets are given a mobile phone with the Kilimo Salama application.
When a farmer wishes to purchase insurance the stockist starts the Kilimo Salama application and registers the farmer in a four-step process
The insurance policy is automatically created on the server and the farmer receives an instant confirmation of his/her insurance coverage via SMS.
Payouts: Automated decision on payoutsPayouts to all farmers under the same
weather stationPayouts directly to the farmer’s phone (M-Pesa)
Farmer confirmation and payout
Making Marketing and Training more effective
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1. Field staff holds the first training
2. At the end of the training the attending famer send keyword-sms to server
3. All farmers are registered into the database linked to an area and trainer
4. Follow up information can be requested by text or via a helpline.
5. Future trainings and simple extension information via mass SMS.
T101
Cut costs on follow up training and mobilisationReal time monitoring and rewarding of field personnel
6. When the farmer buys the product she uses her phone number and she is recognised as linked to t101 = Joseph.
Product design – removing the entry barrier
• Entry barriers: lack of financial literacy, lack of trust
• Create “entry level product” that allows farmers to “try out” insurance
• Pay as you go
• Over time, farmer can move towards higher level products
cove
rag
e
premium
Affordability – partnership with input suppliers
• Risk is high and therefore the premium for a reasonable risk coverage is high and for many farmers beyond their affordability
• Partnerships with the private sector as sustainable alternatives for subsidies
• Input companies have interest in success of farmers
Partnership with private sector suppliers
Affordability – added value services
Reducing transaction cost: Weather index based insurance
• Index model
– Relation weather conditions & crop growth using agronomic models
– Historic weather data used for pricing risk
• Automated weather station measures conditions
• If weather station shows loss, then all insured farmers are paid, irrespective of on-farm loss
• No farm visits = low transaction costs
Automated Weather stations
• Send data every 15 minutes to central server over GPRS network
• Store and resend data in case network is down
• Solar powered
• Remote monitoring of weather station operations
• Most weather stations are placed on public ground (schools)
• Data are also provided to local schools, used in geography classes