Insurance companies rely on catastrophe models to provide reliable estimates of loss, whether for managing risk over the long term or for understanding their loss potential in real time as an actual event unfolds. However, the reliability of model output is only as good as the quality of the exposure data used as input.
High-quality exposure data is essential for effective catastrophe risk management, improved underwriting and reinsurance decisions. Furthermore, rating agencies are now requesting companies report in detail on the quality of their exposure data.
The latest A.M. Best Supplemental Ratings Questionnaire, for example, requests that companies report if data elements essential for estimating catastrophe risk–such as geocoded location, construction, occupancy, year built and other data–are specified for individual risks.
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