Which of the following best describes the Law of Large Numbers in insurance?

The Law of Large Numbers is a fundamental principle in the field of insurance that states that as the number of similar risks increases, the actual losses experienced will more closely approximate the expected losses. This principle supports the predictive nature of insurance calculations, allowing insurers to estimate future claims and set premiums more accurately.

When a significant pool of similar risks is insured, random variations in claims will average out, leading to more predictable outcomes. This predictable nature of losses helps insurers manage their financial resources more effectively and ensures that they can remain solvent while meeting policyholder claims. By understanding this concept, insurers can balance the premiums they charge with the expected payouts, leading to financial stability within the insurance industry.

The other options do not accurately reflect the Law of Large Numbers' principles. They either discuss aspects of insurance that are not directly related to this statistical law or define concepts that relate more to overall insurance practice rather than specifically to how predictable losses become with an increased number of risks.