What does the "law of large numbers" refer to in insurance?

The law of large numbers is a fundamental concept in insurance that describes how, as the size of a sample increases, the actual outcomes (or results) will increasingly align with the expected outcomes. This principle is crucial in the context of insurance because it helps insurers predict losses and assess risks more accurately when they have a larger volume of data.

In practical terms, this means that when insurers pool together a large number of policies, they can better predict the likelihood and cost of claims based on historical data. For example, if an insurer has a large number of insured individuals, the average loss experienced by this group will be closer to the expected loss calculated using statistical methods. This predictability allows insurance companies to set premiums more effectively and ensures the stability of the insurance market.

The other options reference important but different concepts. One mentions predictions of risk, which is a component of the law but does not capture the essence of how sample size impacts actual outcomes relative to expectations. Another choice discusses limits on claims, which does not relate to the statistical principle at all. Lastly, the calculation of reserves refers to financial management aspects of insurance, unrelated directly to the statistical reasoning behind the law of large numbers. Thus, understanding the precise implications of the law of large numbers is