Presenting a large and complex property portfolio to the insurance markets is a challenge. Loss experience, stability of operations, and a good understanding of the operational hazards—as well as the external exposures to the portfolio—all come into play.

The fact is: Poor information = greater uncertainty = larger premiums.

Exposure to catastrophic natural hazard (CAT) events such as earthquakes and hurricanes is now evaluated and quantified by insurers using catastrophe models that have been developed using the best science and engineering available. These models, which are now mainstays in the marketplace, rely on descriptive data inputs to calculate damage projections.

Every structure is unique—located in a specific spot and built at a certain time, from unique materials, and according to local building codes. Every structure will behave differently during a CAT event and, consequently, damage projections will be unique. Based on the data provided, the CAT models assign vulnerabilities to properties and, eventually, develop a composite portfolio view that, when combined with the hazard level, results in a level of overall risk and will influence premium.

However, these estimates are shrouded in uncertainty. There is uncertainty around the frequency and severity of an event impacting a portfolio. There is also uncertainty around the models’ understanding of the actual vulnerability of each structure within the portfolio. Poor quality input data that does not account for or accurately reflect relevant construction and location factors will result in greater uncertainty and bring less than optimum results.

How Marsh Risk Consulting Can Help

There is a better way: High quality data = less uncertainty = appropriate premiums.

Marsh Risk Consulting’s natural hazards and analytics team is experienced with multiple CAT models and, utilizing a well-defined process, helps organizations to make more informed decisions around the natural hazard risks facing their operations.

Our experts understand structures, catastrophic events, and the benefits of presenting property portfolios accurately to insurers. In the first instance, MRC will identify a portfolio’s loss drivers using modeling results. MRC will then determine, through on-site surveys, the structural components for each location. This is undertaken in order to accurately define each structure in terms of a wide range of primary and secondary building characteristics—critical to the CAT model’s results—that are fully validated and documented. This process provides for a refined building description, reducing the uncertainty around a building’s performance.

Depending on how the insurance program is presently structured, annual premium savings are not uncommon. More importantly, the improvements and benefits realized now should continue every year unless there is a significant change to the property portfolio. Furthermore, once high challenge locations (loss drivers) are assessed, properly described, and coded for modeling purposes, they will not have to be revisited year after year. By engaging MRC and our property portfolio modeling process, organizations can be ensure that they have the expertise and data required to reduce decision making uncertainties and improve financial and operational performance.

To learn more about how MRC’s natural hazards, modeling, and analytics services can add value to your property portfolio risk management strategies, please contact:

Robert Smith – Chicago
+1 312 627-6076

Or, these regional experts:

Edward Haas – New York
+1 212 345-6559

John Koester – Washington, DC
+1 410 347-3637

Rich Wall – Atlanta
+ 1 404 995-2976

Keith Kremkow – Chicago
+1 312 627-6748

Mike Dyrness – Los Angeles
+1 213 346-5566