Which level of abstraction should be used when historical data from the past five to ten years is available for a loss event?

When considering the use of historical data spanning five to ten years for analyzing a loss event, employing the highest level of abstraction, which is Loss Event Frequency, is particularly advantageous. This approach allows for a broad understanding of how frequently specific loss events have occurred over time, utilizing the extensive dataset to provide a comprehensive analysis. By focusing on Loss Event Frequency, it becomes easier to identify trends, patterns, and the overall risk landscape related to potential losses within the organization or sector being examined.

High-level abstraction allows analysts to effectively aggregate data and derive insights that can inform risk management strategies and decision-making processes. Additionally, conducting analysis at this level supports a more generalized view, which is often necessary for strategic risk assessments that may influence policies or resource allocation.

In contrast, using lower levels of abstraction would limit the ability to leverage the historical data fully, potentially leading to a narrowed scope that might not capture the broader context of loss events. Thus, focusing on the highest level of abstraction aligns with the goal of maximizing the utility of the historical data available for informed risk analysis.