Technology has advanced to the point where an individual risk can be analyzed as part of an automated underwriting process. Furthermore, insurers can minimize the impact on the current underwriting workflow by capturing the data required for sound catastrophe risk management as part of the replacement-cost estimation process.
Many policies today are still underwritten using hazard-based assessments of catastrophe risk. These approaches, including rating territories and distance-to-coast, are insufficient because location is the only aspect of the property’s risk profile considered. The use of these metrics can be counterproductive. A distance-to-coast analysis may suggest underwriting a less attractive risk three miles from the coast, while rejecting a better risk 500 feet from the coast.
To achieve reliable results, the input data needs to be detailed and high-quality. Fortunately, much of the property-specific data needed for catastrophe risk assessment is also needed to estimate replacement costs, making it easy to collect property information relevant to catastrophe risk during the replacement-cost estimation process.
Leveraging the property-specific data captured during the replacement-cost estimation process provides value for portfolio-level catastrophe modeling, even if catastrophe risk is not analyzed during the underwriting process.
Catastrophe-modeling data extracted from insurers’ policy management systems can be enhanced, augmented, or replaced with data available in the replacement-cost estimator. By extracting property data directly from the replacement-cost estimator, insurers can be more confident their analyses are based on detailed and reliable building information for each risk. Furthermore, before the data is extracted for catastrophe modeling, replacement-cost estimates for all properties can be recalculated to ensure they are based on current building costs.