What principle does the "law of large numbers" in insurance illustrate?

The principle illustrated by the "law of large numbers" in insurance is that as the number of exposure units increases, the predicted loss becomes more accurate. This statistical concept suggests that with a larger sample size, the average loss will be closer to the expected loss rate calculated from historical data.

In an insurance context, this means that when an insurer covers a larger pool of policyholders, the random variations in individual loss experiences tend to even out, leading to a more reliable estimate of total losses. Thus, insurers use this principle to set premium rates and maintain financial stability, as it helps them confidently predict future claims based on accumulated data from large groups rather than relying on smaller, potentially misleading samples.

This understanding is crucial for effective risk management and ensuring that insurance premiums are adequate to cover the expected payouts, avoiding under- or overestimating the costs associated with claims.