What mathematical principle is used by insurers to predict losses and set premiums?

The Law of Large Numbers is a fundamental mathematical principle used by insurers to predict losses and establish premiums. This principle asserts that as the number of insured units increases, the actual loss experiences will approximate the expected losses more closely. In simple terms, it suggests that larger samples provide more reliable outcomes.

For insurers, applying this law means that they can use historical data from a large pool of similar instances to forecast future losses with greater accuracy. By gathering enough data, they can estimate the likelihood of certain events occurring, which in turn helps them to price their policies appropriately and maintain financial stability. As a result, premiums can be set based on established probabilities rather than speculative figures, allowing insurers to effectively manage risk and ensure that they can cover claims when they arise.

The other options represent important concepts in the insurance field but do not focus specifically on the predictive nature of large data sets. Indemnity pertains to the principle of compensating losses, the underwriting principle involves assessing risk for individual applicants, and loss ratio is a metric that reflects the relationship between losses and premiums collected. While these concepts are integral to the insurance process, it is the Law of Large Numbers that fundamentally enables insurers to make reliable predictions about future claims.