What enables an insurer to forecast the expected extent of future losses?

The correct choice highlights the importance of having a sufficient number of exposures to similar risks, along with the use of historical patterns and trends, which is fundamental for an insurer in forecasting expected future losses. Insurers rely on statistical analysis derived from past data involving policyholders who present similar risk profiles.

By employing methods such as loss frequency and severity analysis, actuaries can determine the likelihood of certain events occurring and the potential financial impact. This data-driven approach allows insurers to establish more accurate reserves for claims, set premiums appropriately, and manage their overall risk exposure effectively.

The other options do not support effective forecasting. Random guessing would lead to uncertainty and potential financial losses rather than reliable predictions. Continuous changes in policies can add complexity to risk assessment, making it harder to forecast losses based on inconsistent data. While customer feedback on service quality is important for customer satisfaction and retention, it does not directly contribute to predicting financial losses related to risk exposures.