Want to Improve Property Insurance Renewals? Start With Your Data
After many years of hearing the message, companies appear to be taking it to heart: Data quality matters. A recent Marsh survey during our The New Reality of Risk webcast series asked participants to respond to this statement: “I’m confident that my organization consistently provides high-quality data on property exposures to our underwriters.”
The results from more than 170 risk executives:
- 77% said true.
- 9% said false.
- 14% said they weren’t sure.
And that is good news.
Since at least in the aftermath of Hurricane Katrina, which struck 10 years ago, insurers, Marsh, modelers, and others have been touting the virtues of data quality when modeling catastrophe (CAT) risks. To see nearly 8-in-10 respondents saying they are practicing what we preach is encouraging.
CAT modeling is a key component of every property placement. It’s often the driving factor in insurer participation, pricing, and terms and conditions — not to mention an important way for you to better understand why you’re buying particular coverage. CAT models are highly sensitive to uncertainty driven by poor or missing data. When you provide underwriters with high-quality data, you can better quantify and qualify the risk being considered, which can result in significant premium savings.
Good data is especially important now because modeling firm RMS just released version 15 of its North American hurricane season model. This release is an update, not a full rewrite, of the model that will bring changes of typically low to moderate impact for organizations. The expected change in modeling results should range between 10% decreases to 10% increases in the average exceedance probability (AEP) and corresponding average annual loss (AAL), depending on an insured’s risk profile.
Generally, modeled losses are expected to show an overall decrease, but some areas may see increases due to new classifications of vulnerability. These include claims from Superstorm Sandy, flood damage to machinery and equipment stored in basements, and new building codes in Florida.
My Marsh colleagues and I recommend that modeling or remodeling be done after the RMS 15 release, especially on windstorm-exposed risks. Doing so will enable you to better understand what’s changed and, more importantly, identify areas of potential data weakness that need to be addressed in order for carriers to get the best modeling result possible.
The bottom line? You should work with your insurance advisors to validate modeling data that increases accuracy, decreases uncertainty, and better informs underwriters and you. Investing in data validation generally yields very solid returns.