What does the Law of Large Numbers explain?

The Law of Large Numbers is a fundamental principle in insurance that illustrates how the predictability of losses improves as the number of exposures or insured units increases. This concept suggests that with a larger pool of risk, it becomes easier to estimate the expected number of losses and the associated costs, leading to more accurate premium pricing and financial stability for insurers.

Essentially, as more policies are written, the randomness of individual losses averages out, allowing insurers to predict their total losses—and consequently their necessary premiums—more precisely. This principle is crucial for insurance companies because it underpins their ability to assess risk and set rates that are both fair for consumers and adequate for covering potential claims.

In contrast, other options do not align with the core concept of the Law of Large Numbers. While it is true that selling more policies can achieve economies of scale and potentially reduce costs, that is not its primary focus. The notion that the probability of loss becomes random does not capture the essence of how the Law of Large Numbers operates, as it relies on the aggregation of data to reduce uncertainty. Lastly, the idea that the total value of insurance policies must be equal is unrelated to the statistical principles that guide risk assessment and is not a tenet of the Law of Large Numbers