What principle states that increased exposure units lead to a closer alignment between actual and expected losses?

The Law of Large Numbers is a fundamental principle in statistics and insurance that asserts that as the number of exposure units increases, the actual outcomes will become more predictable and will converge towards the expected outcomes over time. In the context of insurance, this means that with a larger pool of insured entities, the insurer can more accurately forecast the total expected losses. This happens because individual fluctuations and anomalies in loss events are averaged out, leading to a more stable and accurate representation of risk.

In insurance, this principle is crucial because it allows insurers to set premiums that are mathematically justified based on the expected loss of a large group rather than relying on a small number of observations, which may be heavily influenced by random variations or unusual events. Ultimately, this principle helps in creating a system where both insurers and insured parties can rely on predictions regarding future claims, fostering trust in the insurance system.