What does the law of large numbers ensure in insurance?

The law of large numbers is a fundamental principle in insurance that helps ensure accurate predictions of losses. This principle states that as the number of exposures (or policies) increases, the observed outcomes will converge to the expected value. In practical terms, this means that by pooling a large number of similar risks together, an insurer can predict the overall loss with greater accuracy.

When a large pool of similar policyholders is analyzed, the random fluctuations in losses tend to even out, allowing the insurer to estimate potential losses based on historical data. This creates a more stable environment for setting premiums and ensures that the insurer remains financially viable by being able to cover claims that arise.

The other choices relate to different aspects of insurance but do not accurately reflect the essence of the law of large numbers. For instance, higher premiums for smaller risks and reduction of coverage limits do not necessarily correlate with the predictive reliability offered by this law, nor do increased claims from fewer payments align with the principle’s aim of minimizing uncertainty through diversification and collective risk assessment.