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Actuarial notation is a shorthand method to allow actuaries to record mathematical formulas that deal with interest rates and life tables. Traditional notation uses a halo system , where symbols are placed as superscript or subscript before or after the main letter.
It is primarily used in the property and casualty [5] [9] and health insurance [2] fields. Generally considered a blend of the chain-ladder and expected claims loss reserving methods, [ 2 ] [ 8 ] [ 10 ] the Bornhuetter–Ferguson method uses both reported or paid losses as well as an a priori expected loss ratio to arrive at an ultimate loss ...
Actuarial science became a formal mathematical discipline in the late 17th century with the increased demand for long-term insurance coverage such as burial, life insurance, and annuities. These long term coverages required that money be set aside to pay future benefits, such as annuity and death benefits many years into the future.
Ultimate loss amounts are necessary for determining an insurance company's carried reserves. They are also useful for determining adequate insurance premiums, when loss experience is used as a rating factor [4] [5] [6] Loss development factors are used in all triangular methods of loss reserving, [7] such as the chain-ladder method.
Milne's new "Carlisle table" marked an epoch in actuarial science. Considering the narrow base of data from which he had to work, it was quite accurate, and was widely adopted by insurance societies. The Carlisle Table was largely superseded by that published by the Institute of Actuaries in 1870. [2]
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The chain-ladder or development [1] method is a prominent [2] [3] actuarial loss reserving technique. The chain-ladder method is used in both the property and casualty [1] [4] and health insurance [5] fields. Its intent is to estimate incurred but not reported claims and project ultimate loss amounts. [5]
Typically burning cost is the estimated cost of claims in the forthcoming insurance period, calculated from previous years' experience adjusted for changes in the numbers insured, the nature of cover and medical inflation. Historical (aggregate) data extraction; Adjustments to obtain 'as if' data: