What assumes the presence of a predictable pattern in large groups within insurance practices?

The law of large numbers is a fundamental concept in insurance that states that as the number of exposure units increases, the actual outcomes will tend to approach the expected outcomes. This law assumes that in large groups, the random variations will average out, leading to more predictable and stable results.

In insurance practices, this principle is crucial because it allows insurers to estimate the likelihood of claims occurring based on statistical data from large groups of similar risks. This predictable pattern helps insurers set premiums and reserve adequate funds to pay future claims, making it easier to manage risk effectively over time.

The other concepts do not encapsulate this idea of predictability in large populations as precisely as the law of large numbers. The law of accidental outcomes, for instance, pertains to individual incidents and does not account for the statistical averaging that occurs in large groups. The principle of non-selection is more focused on underwriting and the selection of risks rather than on group behavior. Lastly, the rule of thumb in underwriting is a general guideline rather than a principle grounded in statistical law, and it doesn't specifically address the predictable patterns necessary for large group analysis.