According to the law of large numbers, how are losses impacted as the number of similar insured units increases?

The law of large numbers states that as the number of similar insured units increases, the predictability of losses improves. This statistical principle indicates that with a larger sample size, the actual losses will tend to average out closer to the expected losses, thereby making it easier for insurers to estimate risks and determine premiums more accurately.

When dealing with large groups, random fluctuations in data tend to balance each other out. This means that the actual number of losses experienced in a larger pool will more closely align with the estimated or expected losses, allowing for better forecasting and risk management. As a result, insurers can set premiums with greater confidence based on historical data, leading to a more stable and predictable insurance market.

This foundational concept is critical in the insurance industry as it underpins the necessity for pooling risk among a larger number of policyholders, which ultimately enhances the insurer's ability to maintain financial stability and effectively manage risk.