What do insurance companies use to determine expected losses?

Insurance companies rely on statistics and the law of large numbers to estimate expected losses, as this approach provides a reliable framework for predicting the likelihood of events occurring over a larger group. The law of large numbers states that as the size of a sample increases, the actual results will get closer to the expected results. This principle allows insurers to analyze historical data from a significant number of policyholders to project future claims accurately.

Using statistical methods, insurers aggregate data on past claims to identify patterns, frequency, and severity of losses. This aggregation enables them to assess risks more accurately and set premiums that reflect the expected payouts. A larger pool of data leads to a more reliable estimation of losses, which is essential for maintaining the financial stability of the insurance company and ensuring they can meet future claims.

While principles like risk aversion contribute to insurance theory, and market trends or customer feedback can provide relevant insights, they do not directly establish expected losses in the same quantifiable manner as statistical analysis and the law of large numbers.