The success of property insurance firms hinges on two distinct underwriting competencies, setting them apart from their less successful counterparts:

1. How accurately can you quantify the risk of an individual exposure? and
2. How well can you assemble a diversified portfolio of those individual exposures to optimize the premium-to-capacity ratio?

Many technology advancements in the past few decades have been dedicated to precisely quantifying individual property exposures. These advancements include high-resolution catastrophe models, hazard maps, topography maps, and aerial imagery. Today, the underwriter’s access to information about an individual property is virtually limitless. With the right integrations, it is possible to identify missing roof shingles, predict the most likely entry point of flood waters, estimate the replacement cost, and determine a fairly accurate loss pick for an individual location.

This trend of location-specific underwriting is absolutely crucial for property insurers, especially those who were crushed by losses from Hurricane Hugo (1987) and Hurricane Andrew (1992). Catastrophe models led the way, and over time, the resolution of models, maps, and analytics meant the triangulation of risk for individual properties became much more accurate.

Yet, while the ability to accurately quantify individual property risks is immensely valuable, it is NOT how we keep score in underwriting!

Year in and year out, we track success not by how well we did from individual locations but by how our overall portfolio did. Loss ratios, combined ratios, return on capacity, and return on capital are all computed based on portfolio losses and gains, and not on whether we successfully underwrote individual locations. Superior underwriting at the individual property level fails if we can’t assemble those locations into a portfolio that optimizes the capacity we have allocated.

We instinctively know this (every underwriter with a property book knows the pitfalls of too much exposure in Florida or too much concentration in Miami-Dade County). And yet, most resources of underwriting effort and time go into filling the pipeline with submissions (from wherever we can get them), underwriting those submissions, and allowing the portfolio to evolve in whatever manner the markets decide. This is a recipe for mediocrity, or worse.

EXPOSURE MANAGEMENT

The most optimal portfolios are those fitting these criteria:

1. Each individual exposure can be accurately quantified for expected loss and probable maximum loss (PML).
2. The scale potential of the opportunity justifies the marketing effort to locate these exposures.
3. The individual exposures minimally correlate to one another.
4. Portfolio losses can be estimated and forecasted with high confidence.

What we typically see are underwriting teams who can execute on items 1 and 2 but fail on 3 and 4. Robust exposure management capabilities built into a core administration system will help insurers optimize their portfolios.

CAT LOSSES DON’T FOLLOW POLITICAL BOUNDARIES

When engaged with underwriting teams creating exposure management reports, we commonly see exposures grouped by political boundaries. These are reports that show how much exposure Florida has, for example. And, for the exposure in Florida, how much of that might be in Miami-Dade County? It is quite common to see reporting maps that look like this:

 

 

 

 

 

 

 

 

https://link.springer.com/article/10.1007/s11069-020-04470-2

However, such a method of categorizing exposure is not practical because natural disasters do not adhere to any boundaries other than the random boundaries the event themselves follow (a wildfire or storm surge does not know to stop at the county or state line). A more effective approach would be to analyze exposures based on high-resolution geospatial analysis.

Take wildfire exposures, for instance. While it is somewhat helpful to know your overall exposure in the state of California, or in a county within California, or even within a zip code in California, that understanding is still too arbitrary to understand your risk concentration. For wildfire underwriting, it becomes critical to understand how many properties are truly within common paths of fires. How many properties are you insuring within a census block or neighborhood? It is critical to understand how to execute on exposure management, but suffice it to say, that with the high resolution geospatial tools available today, the ability to craft exposure guidelines that can measure the aggregation of risk around each and every insured property is becoming table stakes. For perils such as wildfire and flood, quantifying the exposure at some radius surrounding each property can proactively prevent risk aggregation.

CONCLUSION

Exposure management is a critical, but often less prioritized, aspect of property insurance. It requires a nuanced understanding of various factors that contribute to risk, such as topography, geography, hazard, and vulnerability. While the ability to accurately quantify individual property risks is important, the ultimate success of an insurer lies in how well a diversified portfolio that optimizes capacity can be assembled. Underwriters should continually strive to refine strategies and techniques in exposure management, keeping in mind that the aim is not merely to avoid risk, but to understand, manage, and leverage it.