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Using Satellites to Make Index Insurance Scalable -- IRI

About the Project

 
Project Name: Using Satellites to Make Index Insurance Scalable -- IRI
Type of Facility Project: Microinsurance innovation grantee
Country of Operation: Ethiopia
Region: Africa
Sub Topics: Business viability, Other channels, Data analysis and processing, Claims, Product development, Improving value, Agriculture
 

Organizational Overview

The mission of the International Research Institute for Climate and Society (IRI) of the Columbia University isto enhance society’s capability to understand, anticipate and manage the impacts of climate in order to improve human welfare and the environment, especially in developing countries.

The IRI has worked on index insurance projects in Africa, Asia and Central America, collaborating with local stakeholders, intermediaries and re-insurers. In Ethiopia, for more than a decade, the IRI has built strong partnerships and in-depth knowledge of the country’s climate, agriculture and relevant institutions.

Consortium members

Oxfam America (OA) is an international relief and development organization that creates lasting solutions to poverty, hunger, and injustice.

OA has been working in the Horn of Africa region since the Ethiopian famine of 1984. Since the 1990s, its work has expanded beyond humanitarian assistance to include long-term community based development. OA has built a strong portfolio of work with microfinance institutions in the country over the last few years. 

OA is the co-lead implementer, along with the Relief Society of Tigray (REST) for the Horn of Africa Risk Transfer for Adaptation (HARITA) initiative, which focuses on climate resiliency and local area development of which the IRI is the lead technical partner. With 17 formal project partners, the HARITA consortium has worked on designing a scalable risk management package for rural people in Ethiopia, including index crop micro-insurance. 

 

Project Description

The lack of comprehensive rainfall and crop data is a key constraint in scaling insurance. Historical data is necessary to calculate the price of insurance, while current rainfall data is needed to verify claims. The conventional approach to develop weather insurance indices is to use field-based rain gauges. However, gauges are subject to tampering and current rain gauge coverage in many developing countries is sparse; installing new gauges is an expensive and time consuming process. Satelli...READ MORE
 

Beneficiaries

The beneficiaries of this project are low-income, rain-fed subsistence farmers who are amongst Ethiopia’s most vulnerable segment of population. These farmers are particularly vulnerable when rainy seasons start late and end early.

About 40% of the targeted 50,000 households are headed by women and about 60% are enrolled in the country’s Productive Safety Net Project, a well established social protection program that serves eight million low income people.

The primary crops grown by the targeted beneficiaries for which coverage is being provided are teff, wheat barley, maize and sorghum amongst others

 

Learning Agenda

  • How can satellite imagery of vegetation be used to validate current index insurance products?  
  • When is satellite imagery of vegetation replicable and scalable? Under which circumstances, for which crops and areas are they accurate? What are efficiency gains for insurers?
  • What is an added value for clients of using satellite imagery of vegetation? To what extent does it reduce basis risk by appropriately identifying locations with payouts in loss years? What is its potential to make the products more affordable, and enable faster payouts in case of rainfall/weather based losses?

Project Status

Key Performance Indicators

Transacted index insurance policies of HARITA project

Year

Transacted index insurance policies

2010

1,308

2011

13,044

2012

About 20,000

Remote Sensing Products Used for Analysis

Working Name of Index

Type of Remote Sensing

Full Name of Index

Name of Producer

How often it provides measurements

Resolution (spatial extent) of measurement

ARC

Rainfall

African Rainfall Climatology

NOAA-CPC

Daily

10km

TAMSAT

Rainfall

Tropical Applications of Meteorology using Satellite data and ground-based observations

University of Reading, UK

10 days

4km

ENACT

Satellite rainfall blended with ground-based rainfall measurements

Enhanced Climatology Time Series

Ethiopian NMA

10 days

10km

EVI

Vegetation

Enhanced Vegetation Index computed from the Moderate Resolution Imaging Spectroradiometer on-board TERRA satellite

NASA

16 days composite

250m

NDWI

Vegetation’s water content

Noramalized Difference Wetness Index computed from the Moderate Resolution Imaging Spectroradiometer on-board TERRA satellite

NASA

16 day composite

250m

 
 
Project Updates
As of February 2012 Data across all of the 83 HARITA sites from the rain gauges was gathered and organized. Farmers and local experts were also asked about years with a low level of rainfall to create a qualitative list. Moreover, an analysis script was written and applied to query satellite databases. This made it possible to compare 12 years of data of an array of vegetation remote sensing products against yield data, ground rainfall observations and remote sensing of rainfall, enabling IRI...READ MORE

Project Lessons

On using satellite technology to scale up insurance schemes Satellite vegetation and rainfall measurements can help reduce the cost of physical validation which can allow index insurance projects grow more rapidly. Index insurance schemes are required to invest significant resources in physical validation, such as the installation of rain gauges. Satellite products offer alternative validation tools which can reduce the...READ MORE
 
 
On added value for clients Satellite imagery of vegetation can improve the coverage quality and lower the cost of the products offered to clients. Satellite products allow index insurance programs to spend less resources on expensive on the ground validation. This makes it possible to expand the outreach of index insurance to low-income farmers in areas with limited rain-gauge data. The products have also demonstrated that they can identify the ind...READ MORE
 
 
On training Sample data, hands-on exercises and visual presentations help illustrate and clarify key messages of training material. Index insurance is a technically challenging topic. After carrying out initial training sessions in 2011, IRI gathered feedback from the participants. The feedback highlighted that participants asked for using more sample data, hands on exercises and more visual presentations (in particular of actual satellite imagery)...READ MORE
 
 
Project page contributor/s:  Pranav Prashad (The Facility)
 
 
Date of last update:  July 2014