Law of Large Numbers (LLN)
This law states that the larger the number of exposures considered, the more closely the losses reported will match the underlying probability of loss. Under the LLN, the insurer knows from experience approximately how many policies will suffer a loss and how severe most of those losses will be. While actual experience may differ from expectation, pooling a large number of policies allows the company to be fairly accurate with its prediction. The simplest example of this law is the flipping of a coin. The more times the coin is flipped, the closer it will come to actually reaching the underlying probability of 50 percent heads and 50 percent tails. See also Degree of Risk, Odds and Probability.
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