In previous blogs I have discussed the
impacts of climate change of weather, with a particular focus on the increased
frequency and magnitude of extreme weather events, such as hurricanes. Even now
much of Wales and South-west England is experiencing floods, while North
America suffers an Arctic cold-spell (to put it lightly). When it comes to calculating the probability
of extreme weather events one industry has a direct financial nexus. The insurance industry.
Insurance is designed to minimize
loss. Many commodities can be insured
ranging from phones to lives. However,
for insurance to function properly the market has to be characterised in a
particular fashion: there has to be a fairly constant percentage of the hazard
occurring and a large client base is required.
For example, a property insurance protecting against burglary, where the
statistics for the number of burglaries in a certain district is readily available
and a percentage of burglaries taking place is easily calculable. From this insurers can calculate the number
of clients that they require to take out the insurance and the price of the
insurance given the number of burglaries they expect to take place in a given
time frame.
Some events cannot be insured against, the
most famous recent example being the 2007 sub-prime crisis. This was a result
of an extremely high volume of mortgage borrowers defaulting on their loans at
a similar time. The insurers who had
taken out credit default swaps based on the AAA rating of the mortgage-backed
securities (MBS), which were created
from the mortgages, could not afford the resulting payouts when these swaps
occurred at the same time.
This “Black-Swan” event is a good example
of how the insurance industry cannot operate when everyone is affected by the
same hazard at once. This is exactly the case with natural disasters.
References-
Engel,
K. and McCoy, P. (2011) The Subprime Virus: Reckless Credit, Regulatory
Failure, and Next Steps. New York: Oxford University Press.
No comments:
Post a Comment