What primarily determines the ideal characteristics of an insurable risk involving the calculation of loss frequency and severity?

The ideal characteristics of an insurable risk are primarily determined by the law of large numbers. This principle states that as the number of exposure units (such as insured individuals or properties) increases, the actual loss experience will converge on the expected loss experience.

In the context of calculating loss frequency and severity, the law of large numbers allows insurers to predict future losses more accurately based on past data. Higher numbers of similar risks enable the insurer to observe patterns and trends, which enhance their ability to set premiums that reflect the risk of loss accurately. This helps ensure that the collected premiums will ultimately cover the losses incurred by the insurer, maintaining the financial viability of the insurance pool.

While the other choices relate to different aspects of risk and insurance, they do not directly address the underlying principle that allows for the systematic calculation of loss frequency and severity. The law of averages describes expected outcomes but is not as foundational as the law of large numbers when it comes to understanding insurance risk. Actuarial value pertains more to the financial aspects of insurance coverage than the characteristics of insurable risks themselves. Random chance reflects the unpredictability of individual loss occurrences, which can be mitigated by applying the law of large numbers in the aggregation of risks.