30 O Hasu and T-K Lehtonen
creating maps; and the question concerning what in the business is called
‘basis risk.’
Data sources
In the design process, a variety of sources are used to assemble information. Typically, this will include historical hazard data, inventory damage
figures, and local expert knowledge from specialists such as agronomists,
hydrologists, and seismologists. Where historical quantitative data is lacking, anecdotal accounts are used: ‘the product design team relies on farmers’ recollections and information from local experts as well as government
and international sources to categorize the level of crop damage caused by
the named peril in each year and geographical area’ (RM: 34).
Determining the structure of coverage and payments
Index insurance transforms all these pieces of information and streams
of visual or quantitative data from satellites and weather stations into a
financial model that makes payouts when a specified threshold is reached
in the monitored data. The payout triggers are defined as a percentage of
the sum insured. For example, a policy can be designed so that the insured
will be indemnified when a region’s cumulative rainfall for the policy period
is under 100 millimetres, with each millimetre below the trigger equalling
2% of the sum insured; thus, 100% of the sum insured is paid out when the
cumulative rainfall is less than 50 millimetres.
The design process begins with constructing a base index that provides
full coverage on the modelled risk events. However, to produce a marketable
insurance instrument, it does not suffice to establish the environmental likelihoods in a given area. For potential policyholders, the high coverage of the
base index is often too expensive. Therefore, the next step in the process is to
redesign the index so that it provides less coverage but is cheaper and better
fits the economic interests between local farmers and the insurer. Thus, as
described by the document (RM: 17), in practice index insurance will usually be saleable only as a product that underinsures the relevant risks.
Mapping
Risk categorisation for the instrument’s purposes is achieved in geographic
terms. The levels of expected average damage are estimated by organising
a region into specified areas with determined risk profiles. The idea is that
when a payout is triggered for an area, all insured farmers within it receive
the same amount of compensation; no differentiation between policyholders
is made. This is the reason why index insurance products do not require
individualised damage evaluations to process payouts. The other side of the
coin is that mapping becomes the crucial activity for making index insurance
creating maps; and the question concerning what in the business is called
‘basis risk.’
Data sources
In the design process, a variety of sources are used to assemble information. Typically, this will include historical hazard data, inventory damage
figures, and local expert knowledge from specialists such as agronomists,
hydrologists, and seismologists. Where historical quantitative data is lacking, anecdotal accounts are used: ‘the product design team relies on farmers’ recollections and information from local experts as well as government
and international sources to categorize the level of crop damage caused by
the named peril in each year and geographical area’ (RM: 34).
Determining the structure of coverage and payments
Index insurance transforms all these pieces of information and streams
of visual or quantitative data from satellites and weather stations into a
financial model that makes payouts when a specified threshold is reached
in the monitored data. The payout triggers are defined as a percentage of
the sum insured. For example, a policy can be designed so that the insured
will be indemnified when a region’s cumulative rainfall for the policy period
is under 100 millimetres, with each millimetre below the trigger equalling
2% of the sum insured; thus, 100% of the sum insured is paid out when the
cumulative rainfall is less than 50 millimetres.
The design process begins with constructing a base index that provides
full coverage on the modelled risk events. However, to produce a marketable
insurance instrument, it does not suffice to establish the environmental likelihoods in a given area. For potential policyholders, the high coverage of the
base index is often too expensive. Therefore, the next step in the process is to
redesign the index so that it provides less coverage but is cheaper and better
fits the economic interests between local farmers and the insurer. Thus, as
described by the document (RM: 17), in practice index insurance will usually be saleable only as a product that underinsures the relevant risks.
Mapping
Risk categorisation for the instrument’s purposes is achieved in geographic
terms. The levels of expected average damage are estimated by organising
a region into specified areas with determined risk profiles. The idea is that
when a payout is triggered for an area, all insured farmers within it receive
the same amount of compensation; no differentiation between policyholders
is made. This is the reason why index insurance products do not require
individualised damage evaluations to process payouts. The other side of the
coin is that mapping becomes the crucial activity for making index insurance