Improve your insurance outcomes with quality property data
The accuracy of any model starts with the quality of the components. The same is true for catastrophe (cat) models in the context of commercial property insurance – inaccurate data can only be expected to produce inaccurate results. Accuracy is vital, and data needs to be trustworthy to evaluate the risk and price insurance correctly. Large commercial property owners need to recognize that controlling the quality of their data and maximizing their inputs for cat models is an essential characteristic of a mature risk management practice.
In the past, secondary modifiers used by cat models were highly scrutinized by the insurance industry due to accuracy concerns, but now high-quality data with referenceable sources has proven vital in maximizing model accuracy. Increases in cat model results for property insurance renewals can be dramatic – from 5 - 125%. One modifier for one property in the right place could not only significantly change the pricing for that property but could potentially swing portfolio level pricing by 20-30%.
The importance of cat modeling and modifiers
Basic information about a property (referred to as primary modifiers) typically includes the occupancy, construction type, square footage, year built, and number of stories. Using only these inputs into a cat model results in a base modeled loss calculation. More granular information about the building (known as secondary modifiers) includes additional detailed attributes about the property, such as roof and building envelope details, proximity to other structures, and whether the structure has a weak first floor. The more that is known about the property, in terms of both primary and secondary modifiers, the more accurate the cat modeling results will be in quantifying the risk.
Cat models are essential for evaluating risk and as inputs into pricing insurance. Organizations that have the most complete and accurate property data have a clear advantage over those that haven’t prioritized data quality.
As the insurance market continues to contract in catastrophe-exposed locations, these models are now critical for underwriters to select and price risks accurately. Carriers in regions like Florida and Louisiana are exiting the market due to massive losses from extreme weather events making the remaining carriers very selective about what risks they underwrite. Accurate cat models enable insurers to accurately underwrite portfolios of risks and subsequently purchase the necessary reinsurance to protect their portfolio in the event of a catastrophic loss.
"Models have become an increasingly large part of the underwriting process, and the data you put into those models must be comprehensive and accurate for best results,” explained a Fortune Global 500 insurer. “Lack of data forces us to assume the worst and almost always results in much more conservative pricing and capacity offerings. Additionally, lack of confidence in client data is a big driver in pricing as the basis of risk is lack of certainty. With more certainty, we see less risk in our offerings.”
How your data impacts your insurance program
Underwriters are increasingly insisting on high-quality data to successfully and accurately quantify risk posed by a commercial portfolio. Better information enables them to evaluate the suitability of a risk and provide more exact coverage and pricing. Insurers use cat models to determine how much reinsurance they should purchase to help protect themselves from a cat-exposed portfolio.
Risk managers are frequently frustrated by not knowing exactly why coverage was denied, their premiums increased, or their coverage changed. Catastrophe models are a critical component when insurers assess cat risk. If a portfolio is cat-exposed, secondary modifier data could be the most impactful piece of information relating to their submission. If a risk manager can deliver high-quality secondary modifiers to their insurer, they will also receive more feedback on how that information impacts their insurance program.
On-Demand model-ready exports
Archipelago has expanded its property risk schema to capture primary and secondary modifiers included in the dominant cat models, AIR and RMS, for both earthquake and hurricane perils. With this data populated on the Archipelago platform, a model-ready input file is generated automatically. It can be exported to the file type of choice with all the detail required to optimize modeling results.
Leverage high-quality data
Poor data quality in property data remains a threat to quality outcomes for risk managers placing coverage in the insurance market. The opposite is also true, and organizations have an opportunity to leverage higher quality data to drive better results. Insurance buyers and providers can benefit from increased accuracy and transparency, and rest assured that if a major windstorm, earthquake, or flood occurs, the risk is accurately estimated and covered.
At Archipelago, we’re focused on changing how commercial property owners, brokers, and carriers manage and use property data. Book a demo here for more information and to see quality property data in action.