What principle is the Law of Large Numbers based on?

The Law of Large Numbers is fundamentally grounded in the statistical concept of probability. This principle states that as the number of trials or observations increases, the empirical probability of an event will converge to its theoretical probability. Essentially, it implies that larger sample sizes lead to more reliable and stable estimates of the expected outcomes.

In insurance, this principle is crucial because it allows insurers to predict losses more accurately. By pooling a large number of similar risks, insurers can determine average loss experiences for a given group, which enables them to price their products more effectively and manage their risk. The predictability gained from the Law of Large Numbers helps insurers ensure that they can cover claims and remain solvent over the long term.

The other choices, while relevant to different aspects of the insurance industry or risk management, do not capture the essence of the Law of Large Numbers as it specifically relates to probability and its implications in the realm of insurance mathematics.