80. Why is having a large number of similar exposure units important to an insurer?
Answer: A
The greater the number insured, the more accurately the insurer can predict losses and set appropriate premiums.
Having a large number of similar exposure units allows insurers to better predict potential losses and accurately set premiums, leveraging the law of large numbers. This statistical principle helps to stabilize risk assessment by averaging out individual variations in loss.
A) The greater the number insured, the more accurately the insurer can predict losses and set appropriate premiums.
This option is correct because it highlights the key benefit of having a large pool of similar exposure units. With more units, the insurer can observe patterns and trends in losses, which enhances their ability to calculate risk and set premiums that reflect the true cost of coverage.
B) The greater the number insured, the more premium is collected to offset fixed costs.
While this statement may have some truth, it does not directly address the main reason insurers prefer a large number of exposure units. Collecting premiums to offset fixed costs is a secondary effect and not the primary reason for predicting losses accurately.
C) The greater the number insured, the more premium is collected to help cover losses.
This option is incorrect as it implies that the quantity of premiums collected is the primary reason for having many similar exposure units. Although collecting more premiums can help cover losses, the main purpose of a large number of units is to improve loss prediction accuracy.
D) The insured increases its market share with every insured.
This statement is not relevant to the context of risk assessment and loss prediction. While increasing market share may be a benefit of having more insured units, it does not relate to the insurer's ability to predict losses or set premiums.
Conclusion
Option A is definitively correct because it encapsulates the fundamental reason insurers seek a large number of similar exposure units, which is to enhance their predictive accuracy regarding losses. Other options, while containing elements of truth, fail to address the core concept of loss prediction and premium setting, which is critical for effective insurance operations.