North Carolina Adjuster Practice Exam 2025 - Free Adjuster Practice Questions and Study Guide

The law of large numbers is a fundamental principle in statistics and insurance practice that states that as the size of a sample increases, the sample mean will get closer to the expected value. In the context of insurance, this principle suggests that when an insurer has a greater number of policies or insured units, it becomes easier to predict the overall level of claims and losses that will occur. This increased volume leads to more accurate statistical estimations, allowing insurers to set premiums appropriately and manage risks effectively.

When insurers have a larger pool of data from which to draw conclusions about potential losses, they can more reliably estimate the frequency and severity of claims. This accuracy helps in creating a balanced rate structure that accounts for expected losses, ultimately stabilizing the insurer's financial performance over time.

The other options presented do not align with this principle in the same way. For instance, while insurers may prefer low-risk clients, this preference does not encapsulate the broader implications of the law of large numbers. Similarly, smaller samples actually increase the variability in predictions rather than reduce risk, and although there may be a correlation between premiums and claims, this relationship does not reflect the foundation of the law of large numbers regarding sample size and prediction accuracy.