Designing index-based insurance for livestock
Francesco Fava
International Livestock Research Institute
1
INDEX-INSURANCE FOR LIVESTOCK IN THE IGAD REGION
MINISTERIAL POLICY ROUNDTABLE & TECHNICAL WORKSHOP
ILRI Campus, Addis Ababa, 24-26 June 2019

GOAL - Offer a timely, sustainable,
safety net against catastrophic
drought shocks
 Provide an opportunity for early response
 Prevent vulnerable to fall into poverty trap
by losing their key productive assets.
 Crowd-in investments from the private
sector.
Rationale for livestock Insurance

Conventional insurance
 Loss Claim Verification
Indemnity
 Very high transactions costs
for verification, etc.
 Moral hazard
Index-based insurance
 It does not insure individual losses
 It is based on an “index” strongly
correlated with impacts (no claims)
 The Index is objectively verifiable,
available at low cost
What is Index-insurance

2008 - IBLI R&D agenda launched,
2010 - First commercial product offered in Marsabit by a consortium of private partners
2011 - drought triggered contracts in all covered areas serving as an important proof-
of-concept indicator.
2012 - IBLI began to scale in Kenya beyond pilot site in Marsabit into Isiolo. Program
launched in Ethiopia
The Index-based livestock Insurance (IBLI)

2015 - Kenya Livestock Insurance Program
(KLIP) issues first policies to 5000 pastoralist
households across Wajir and Turkana.
2016 - KLIP has further scaled provision of
IBLI across 8 counties (18k households)
2017 - Increasing momentum toward scale,
particularly with substantial payouts (over 7
million USD) in 2016/2017
2018 - Government of Ethiopia discussing
scaling IBLI program, design efforts in
Uganda, Somalia, Niger and Senegal
The Index-based livestock Insurance evolution

1. Precise contract design;
2. Evidence of value and impact;
3. Establishing informed effective demand;
4. Low cost, efficient supply chain;
5. Policy and institutional infrastructure.
HOW A GOOD SCIENTIFIC IDEA BECOMES AN EFFECTIVE
OPERATIONAL PROGRAM?
Pillars

Index Insurance is a variation on
traditional insurance
1. Indicator (e.g. rainfall, field data, NDVI, etc.)
2. Index (correlated with the risk)
3. Payouts/Indemnities
WHY SOME DESIGN WORK?
AND SOME OTHERS NOT?
How Index-Insurance works

1. Satellite Indicators
Rainfall
– Station-data limited
– Accuracy issues
– Meteorological drought
Vegetation indices
– NDVI (or EVI, fAPAR)
– Available from many satellites
– Agricultural drought
Alternatives indicators
– Soil moisture
– Evapotranspiration (from LST)
cimss.ssec.wisc.edu

1. Satellite Indicators - NDVI
NIR
red
Indicator of the presence/amount of green vegetation

2. Index design
NDVI
Response
Function
Mortality
Chantarat, Mude, Barrett and Carter (2013, JRI)
The Asset Replacement Index Design
 Response Function: livestock mortality data modelled from NDVI
 Asset Replacement: Pays out when livestock deaths are predicted in an area based on an
empirical function
Nice but…
Limited mortality data
availability for scaling-up,
issues with data accuracy
Why replacing rather than
protecting livestock (much
cheaper)?

The Asset Protection Index design
2. Index design
Seasnal forage scarcity
Vrieling et al.,
2014, IJAEG
Standardization and deviation
from ‘historical’ mean
Temporal accumulating
Seasonal cumulated NDVI
NDVI spatially aggregated
1-10 May 2011
MODIS NDVI image (10 day)
Spatial
aggregation
400 km
Response function:
Pays out when forage
availability during the rainy
season is lower then normal
 ealier!
Asset protection
It insures the cost of keeping
the animal alive
 lower!
Data for calibration are not
necessary

3. Payouts/Indemnities
Proportional do the severity of forage scarcity
Payout function
LESS FORAGE
MOREPAYOUTS
When to trigger payouts, with what
frequency, how big?
Impact on premium!

KLIP Product in Kenya
 Covers 5 Tropical Livestock Units for
targeted households. Total covered
value is Ksh 70,000
 Payment triggers below 20th percentile
(every 5 seasons).
 Two risk periods (long rains and short
rains) with payouts in June and
December
3. Payouts/Indemnities

How to design a good product?
Making the right choices
 Understanding the local context,
needs, drought impacts mechanisms
 Use well-established and simple
indicators (quality and awareness)
 Design quality assessment processes
and respond to stakeholders
feedbacks

The Prosopis dilemma
Are NDVI-based Indices affected by the presence of invasive non-palatable species
such as Prosopis?
 NDVI is a greenness indicator. It is NOT related to the quality of forage
 However, the Index is designed to minimize the impacts of species variability with
the objective of detection drought.
1. Masking non usable areas (low interannual variability, signal or using land cover
maps)
2. Averaging (spatially) over large areas (units): local changes in composition have
minimal impacts on the averaged NDNVI
3. Comparing each unit with itself over time: the reference for the detection of
forage scarcity is the historical average in the same location (i.e. same type of
rangelands).
The argument theoretically is sound. Practically no evidences of impacts on the Index.

better lives through livestock
ilri.org
THANK YOU!
f.fava@cgiar.org
THANKS!
f.fava@cigar.org

better lives through livestock
ilri.org