What is the impact of the law of large numbers in insurance?

The law of large numbers is a fundamental principle in insurance that states that as the number of exposure units (in this case, insurance policies) increases, the actual loss experience will converge to the expected loss experience. This convergence allows insurers to predict losses more accurately based on historical data and statistical averages.

When an insurance company sells a large number of similar policies, the variability in loss experience decreases, making it easier to estimate the average loss and set premiums accordingly. This results in more predictable financial outcomes and reduced uncertainty in premium pricing, leading to more stable operations for the insurer.

Thus, this principle supports the idea that having a larger pool of insured entities helps insurers manage risk better and set pricing that reflects the anticipated losses effectively.