MR Microinsurance_2012_03_29.indd - International Labour ...

100 Emerging issues
4.3.1 Weather data
Data are pivotal to the development of insurance products. In the informal
economy, data on customers – let alone data series – are almost non-existent.
With risk-related data, especially weather data, the situation is often no better.
The sparse data available in developing countries makes it particularly difficult
for microinsurers. To develop indices for weather insurance, meteorological
data should span a period of 30 years. It is practically impossible to develop products
and relevant triggers using time series of 10 years or less. Missing data can be
extrapolated using computing processes, which create realistic approximations to
real conditions (Corbett, 2006), though the use of calculated data is difficult,
particularly in microinsurance.
In a world in which an awareness of the importance of insurance must first be
created, abstract figures and formulae can contribute to uncertainty. For example,
drought cover in Ethiopia (see Box 4.3) used data from just 26 weather stations.
It is not easy to convey to a farmer that the value to which the agricultural
cover refers was measured some distance away from his plot. One solution is to
increase the number of weather stations so that they are closer to more farmers,
but there is certainly a cost involved, and there is no consensus as to how close to
each other the stations should be.
Another solution may be remote-analysis methods, which are expected to
make it easier to design relevant indices in the future. Developments such as
area-wide satellite images and aerial photographs of a region should improve
crop yield and loss estimates, giving a boost to agricultural microinsurance. It
remains to be seen whether it will be easier or harder to explain such an approach
to farmers.
4.3.2 Index-based solutions
To manage large volumes of small claims, index covers are generally easier to
handle than indemnity-based ones. The latter are time-consuming and expensive
as losses have to be assessed and settled individually. With index covers, a specific
trigger (e.g. temperature, rainfall and wind speed) is agreed upon. If this
threshold is reached, a payout is made, which streamlines the claims settlement
process. Payments are made regardless of how big the actual loss is for the
insured.
However, there can also be negative effects. Since the loss may not be covered
in full, as it would be with an indemnity cover, this gives rise to a basis risk for
the insured and a reputation risk for the insurer. For example, in an index cover
for agriculture, basis risk can occur in two ways: