In group insurance, which factor, all else equal, improves the accuracy of loss projections due to sample size?

In group insurance, which factor, all else equal, improves the accuracy of loss projections due to sample size?

• A. Financial strength of the group
• B. Size of the group
• C. Turnover rate of the group
• D. Provisions in the policy

Answer: (B)

Larger sample size reduces sampling variability, making loss projections more reliable. In group insurance, projections are based on observed claims, and the more insured lives you have, the more data points you collect. The law of large numbers means that as the group grows, the average outcome converges toward the true expected loss, so the estimate becomes steadier and more accurate. Other factors like financial strength, turnover rate, or policy provisions affect solvency, exposure patterns, or contract terms, but they don’t increase the amount of data or directly reduce the random variation in observed losses. A bigger group smooths out year-to-year swings and gives a truer picture of expected losses.

Larger sample size reduces sampling variability, making loss projections more reliable. In group insurance, projections are based on observed claims, and the more insured lives you have, the more data points you collect. The law of large numbers means that as the group grows, the average outcome converges toward the true expected loss, so the estimate becomes steadier and more accurate. Other factors like financial strength, turnover rate, or policy provisions affect solvency, exposure patterns, or contract terms, but they don’t increase the amount of data or directly reduce the random variation in observed losses. A bigger group smooths out year-to-year swings and gives a truer picture of expected losses.