A New Crystal Ball
How RMS is helping clients improve underwriting by predicting what perils a specific location faces.
Insurers have traditionally relied on the past to predict the risk from catastrophes in the future, but RMS has a new way for underwriters to explain the risk a specific location might face—even when there’s not much loss history in that area. Elizabeth Couchman, senior product manager of underwriting solutions at RMS, said the company’s new Underwriting Toolkit is helping insurers improve their underwriting decisions and better price their policies.
BEST’S REVIEW: How does the new Underwriting Toolkit work?
COUCHMAN: The Underwriting Toolkit is a new application to help insurers assess the risk of specific locations for a range of natural hazards. It allows them to determine whether they want to underwrite certain risks, and if so, what rate they should technically be charging. Currently, clients can assess the risk from U.K. flood, storm surge and windstorm. During the second phase, to be undertaken next spring, we’ll be adding European earthquake and wind to the suite.
Insurers traditionally use catastrophe models for portfolio management purposes, so they can identify where they have large accumulations of risk, and claims data to help determine pricing. Due to the heavy streams of data that are run through the models, it takes time to generate output which is often not appropriate for underwriting. As a result, there tends to be a disconnect between portfolio management and underwriting. The new Underwriting Toolkit brings the two disciplines together, reduces processing time and gives underwriters the results they need at their fingertips.
BR: What is driving the need for it?
COUCHMAN: Many insurers have experienced unexpectedly high losses from an individual policy as they didn’t fully understand the risks to that location from natural catastrophes. This is partly due to the resolution of the data they used. For example, the risk to one part of a postcode or ZIP code can be very different from elsewhere in the postcode, particularly for perils such as earthquakes and floods, as the risk can vary from one side of the street to the other. Also, insurers use a mixture of simple datasets—often produced by government agencies—and claims history to determine the risk and set the premium. However, history isn’t always a guide to the future as it doesn’t tell you about the extremes, and for regions where you don’t have much claims data.
That’s what cat models are good at, but generally, these are only used for exposure management once a policy has been written and they tend to only be run periodically. Therefore, to avoid taking on bad risks or pricing the risk too high or too low, insurers want the science of cat modeling to be available to their underwriters and embedded in the underwriting system.
BR: How does it differ from other technology products on the market?
COUCHMAN: The Underwriting Toolkit enables U.K. and European insurers to accurately assess the risk and obtain technical rates for multiple perils—and soon multiple countries—at the click of a button. Other solutions in the market enable insurers to assess the risk from a single peril or provide metrics at a coarser resolution such as postcode, which are often not derived from fully probabilistic catastrophe models.
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