What does the Law of Large Numbers state regarding insurance?

The Law of Large Numbers is a fundamental principle in insurance that asserts that as the number of similar exposure units increases, the actual loss experience will get closer to the expected loss experience. This means that with a larger pool of policies, insurers can predict future claims more accurately.

When insurers underwrite a significant number of similar risks, they can average out the randomness of individual claims. In smaller pools, individual outlier claims can skew the data, making it difficult to estimate losses reliably. By increasing the quantity of insured units, the insurer can smooth out this variability, thus enhancing the reliability of estimates and ensuring that they are aligned with statistical probabilities. This principle enables insurers to set premiums accurately based on the likelihood of claims, ensuring stability and sustainability in the insurance market.

The context of the other options does not align with the Law of Large Numbers, which is focused on the predictability of losses rather than profit, pricing strategies, or the relationship between claim sizes and payment likelihoods.