What principle does the Law of Large Numbers illustrate in insurance?

The Law of Large Numbers is a fundamental principle in statistics and insurance that suggests as the number of similar risks increases, the predictability of outcomes also increases. This principle indicates that when insurers cover a large group of similar risks, they can more accurately estimate losses, set premiums, and predict future claims.

In practical terms, by pooling a considerable number of similar risks, insurers can analyze historical data and glean insights into how many claims will likely occur and the costs associated. This leads to more stable and reliable underwriting, allowing for sufficient reserves to cover anticipated losses while ensuring that premiums remain appropriate for the level of risk.

In contrast, the other choices are less accurate. Individual calculations for insured values do not reflect the overarching trend of risk pooling, while the notion that insurers must avoid grouping similar risks contradicts the core benefits of the Law of Large Numbers. Lastly, while a higher number of claims could influence premiums, it doesn't illustrate the principle of predictability that the Law of Large Numbers emphasizes.