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Essay / Research Paper Abstract
This 5 page paper looks at how statistics are used in the insurance industry, looking at the type of statistics that are used for different insurance policy types and how the statistics are used as well as why accurate interpretation is important. The bibliography cites 2 sources.
Page Count:
5 pages (~225 words per page)
File: TS14_TEstatinsure.rtf
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Unformatted sample text from the term paper:
they will receive a payment that will compensate them for the losses that they suffered. This is a thriving business and operates on the basis of pooling risk; making individual
risk acceptable. In order to understand how it is possible to ensure that insurance firms can remain profitable at the same time as meeting potential claim obligations it is important
to understand how insurance operates with the foundation of the concept reliant on accurate statistical collection and analysis. There are many types
of insurance which pay out on different types of events; auto insurance pays out if there is damage to the car, or if there is damage caused while driving the
car to other drivers vehicles. This is taken out to protect the policy holder and as a way of covering a potential liability to a third party. Health insurance pays
out when specific conditions are met concerning ill health, so it is a protection and life insurance pays out when the insured dies. The policy holder makes payments to an
insurance firm and if the event occurs, within the period for which the insurance policy is valid (the term), the policy holder, or the beneficiary, will receive a payment. For
some policies, such as life insurance policies, this is a fixed amount, for other policy types, such as health or auto, it may be variable spending on the event and
the costs incurred by that event. Different events may have a different potential for occurrence; these can be assessed with the use of statistics (Howells and Bain, 2007).
The way that an insurance firm will determine the level of the premium that is payable will depend on the likelihood of an event
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