What principle states that a large enough pool of similar risks allows for better loss measures?

The principle that states a large enough pool of similar risks allows for better loss measures is known as the Law of Large Numbers. This principle is fundamental in fields like insurance and finance, where it underlies the idea that as the number of observations increases, the average of the observations tends to converge on the expected value. In insurance, this means that the more policies an insurance company writes for similar types of risk, the more accurately they can predict future losses and set appropriate premiums.

This principle facilitates the pooling of risks, allowing insurers to better understand the likelihood of claims and ultimately stabilize their financial outcomes. By aggregating a large number of similar risks, insurers can smooth out the variability of losses that might occur in any given year, relying on statistical regularities. Consequently, they can operate more effectively and efficiently, ensuring they have sufficient reserves to cover claims while also making a profit.

The other options, while related to risk assessment and management, do not capture the essence of how increasing the number of similar risks improves prediction and measurement of losses as effectively as the Law of Large Numbers does.