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Competing in the insurance market through differentiation, and demonstrating knowledge and expertise to a client, are central to so many business strategies in this industry. The client values the insight an insurance business delivers on their exposure which is reflected in their premium. Sometimes, taking the regular model output view of risk is exactly what’s called for. But to demonstrate this differentiated offer, what about a view of risk for a specific class of buildings, or even just one building?

Miami South Beach

Miami South Beach

By contributing your own vulnerability data into a model, you can deliver a custom view of risk that can get you to a new granular level, whether it is for a specific twenty-story apartment block on Miami Beach or a hundred “big-box” stores that share similar characteristics. With this specialist view, you can differentiate your offer in the eyes of your customer, and generate a “win-win” situation of better downstream pricing for the insured, and profit opportunities for your business.

For many insurers, reinsurers and brokers, there is no shortage of custom vulnerability data. Data is collected from risk assessment and loss control inspections, either using their own or third-party inspectors. Some of these inspections that focus on properties in the top ten percent of a business’s portfolio can cost up to $5,000 or even $10,000 per inspection and run to five hundred data points per building.

What happens to this data? The inspector will compile a risk engineering report, which will be passed to the underwriter, who is then responsible for acting on this data. Much of this can end up as a manual workaround, outside of the modeling or general business workflow. A busy underwriter who may not totally understand the implications of the report may overlook important aspects contained within the findings.

Without the data being included into modeling and into a subsequent Exposure Data Model (EDM), or the right conclusions drawn, the substantial investment made in loss control inspections and reporting will be unrealized. This data needs to be embedded into the workflow and used within the modeling process, which requires the ability for the captured data to be entered for modeling and for customized output to be generated – using an approach called open vulnerability modeling.

Open Vulnerability Modeling

Open vulnerability modeling is exactly as described, RMS allows users of its RMS RiskAssessor™ custom vulnerability solution to integrate their own distinct view of vulnerability into their modeling workflows. Using RiskAssessor means realizing the investment your business is making in collecting custom vulnerability data, acting as a tool to collect, and centralize all the data, together with the opportunity to expand the range of variables you are collecting data for. And rather than sitting outside of your modeling workflow, it is integrated within it, to help continually refine your view of risk.

RiskAssessor currently includes the ability to generate custom vulnerability relationships for the U.S. hurricane wind peril, and offers almost quadruple the number of variables compared to the inclusion of standard hurricane model secondary modifiers. These variables all represent data capture points that anyone from a site inspector to an engineer or a catastrophe modeler can understand and use to effectively represent a structure. Using RiskAssessor, a user can now capture the fact that a building has 90 percent coverage of glazed openings for instance, a vital factor for assessing hurricane risk.

The majority of the variables available in RiskAssessor are unique compared to RiskLink or allow for additional detail. The variables look at building geometry, with the explicit representation of different plan shapes and additional corners that change wind load distributions. It can take into account the difference between varying quality and rating levels for individual components such as the roof, cladding or glazing, and represent the glazed opening area coverage on a building.

Set-up time to customize a view of risk and implement it in the model can take as little as five minutes, and a custom vulnerability curve can be easily compared with the standard curve in the modeling workflow. Aided by RMS inventory research that provides typical building characteristics for a given combination of region and primary characteristics, a user can quickly start to unlock credible risk differentiation across their portfolio.

The effect of including custom vulnerability data on a customer’s premium and on profitability can be dramatic. We have seen users who have spent five minutes using public mapping sources to collect basic assessment data, reduce the risk of an individual location by 50 percent or more, resulting in significant cuts to a customer’s premium.

Although RiskAssessor allows for a per-building approach, generating a customized EDM for a class of properties, such as “big-box” stores sharing similar building characteristics, offers the opportunity to demonstrate your differentiated approach. Once created, these vulnerability curves can be re-used over and over again for any EDM, and genuinely represent your unique view of risk for a class of buildings across your portfolio.

What could this approach mean for your business? Some RiskAssessor users are moving to specialize in types of buildings where they know that using a detailed representation of vulnerability will make a significant difference compared to the standardized model output, and can credibly and confidently expand their business. To find out more, watch our short RiskAssessor video, or download our datasheet.

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Kevin Van Leer
Kevin Van Leer
Senior Product Manager, Model Product Management

As a senior product manager in the Model Product Management group at RMS, Kevin is responsible for RMS climate-peril products for the Americas, including wildfire and custom vulnerability analytics. Kevin has been actively involved in model releases for both severe convective storm and hurricane models over the last four years at RMS. Kevin holds a master’s degree in atmospheric science from the University of Illinois at Urbana-Champaign, where he authored a thesis on tornado-genesis and severe convective storms, and a bachelor’s degree in atmospheric science from Purdue University. He also holds the Certified Catastrophe Risk Analyst (CCRA) designation from RMS. Kevin is a member of the American Meteorological Society (AMS), a mentor for the AMS Board of Private Sector Meteorologists, and a voting member of the ASCE Standards Committee on Wind Speed Estimation in Tornadoes.

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