Mark Twain is credited with saying, “Everybody talks about the weather, but nobody does anything about it.” That’s no longer true.
Well before the climate change debate focused the world on meteorological threats, insurance companies were well aware of the risks associated with extreme weather events. What is less understood is how technology and weather science have evolved to help predict and warn of approaching events, giving advanced notice to alter course and relocate to safety. And now, when sophisticated, highly specific weather data is integrated with high-resolution geospatial imagery, artificial intelligence and telematics, the results are exciting and unprecedented. Consider the merging of high-quality weather information with property imagery at the ground level or the blending of surface conditions, atmospheric conditions and driving patterns. These advancements in weather technology and innovation show that, today, somebody is doing something about the weather.
Weather and Insurance
Weather has a wide-ranging impact on the P&C industry and its policyholders, namely catastrophic and other property damage events as a result of a hurricane or isolated storms producing hail or tornadoes. Events that affect large populations such as wildfire and flooding have been dominating headlines over the last decade, with record-setting payouts in the billions of dollars. These frightening scenarios are just some of the obvious ways in which insurers and their customers are affected by weather.
Insurance is all about gauging the likelihood and degree of risk and transferring the exposure by charging appropriate premiums in exchange for protection. Therefore, insurers and their expert risk modeling partners need to be rigorous when it comes to assisting with rate-making, pricing, accepting/rejecting risks and deciding how much exposure to take in a given geography or how much premium to cede to reinsurers. Each of these critical decisions is made and projected into the future and has tremendous impact on profitability when disastrous events do happen.
Beyond Just Weather: Climate Change
According to Swiss Re, the effects of climate change threaten to cut the world’s economy by $23 trillion by 2050. In the U.S., wildfires, hurricanes, tornadoes, winter storms and extreme temperatures were among 20 weather and climate disasters in 2021 that each cost $1 billion or more, totaling $145 billion and killing 688 people, according to the National Oceanic and Atmospheric Administration (NOAA).
These events highlight the need for businesses, communities and individuals to prepare and react. In addition to the frequency and severity of weather events, there is also an increase in secondary perils associated with weather -- including flooding, wind and hail.
According to a Deloitte study, most U.S. state insurance regulators believe all insurers will face heightened risks -- physical, liability and transitional -- over the medium and long term. Half of those surveyed believe climate change will have a high or extremely high impact on coverage availability and underwriting assumptions. For those that get it right (the product, the pricing and the reinsurance), there's a market ready to buy. For those that get it wrong, there could be significant losses.
Despite these difficulties, insurers also must balance selling and underwriting new business to remain competitive and maintain and gain market share.
See also: Extreme Weather, COVID, Home Claims
Modeling Risk
Insurance carriers tend to model future risk on past occurrences, where mounds of historical weather data are relied on to make those decisions. This, coupled with risk modeling sciences, aids in planning and calculating forward. Yet, climate change, along with the increase of property located in harm’s way and the higher costs of materials to repair and replace structures, converge to suggest the need for even more predictive efforts. The emergence of increased capabilities for insurers to ingest data, greater precision in geospatial mapping and real-time data are allies in the battle for managing risk.
Given all the importance and rigor within the industry however, little is known about just how weather data is developed – at least among insurance executives and other key decision makers. After all, weather information is essentially “free” and supplied through governmental agencies like NOAA (National Oceanic and Atmospheric Administration) and the National Weather Service, which gather information from satellites, radars and other meteorological sensors. Think of this as the raw material that is repackaged, sold and distributed in places like your favorite weather app. Weather providers use this very information to, in turn, be incorporated in real-time weather analysis algorithms, predictive models, forecasts and ultimately an insurer’s decision-making process.
Weather Data and Use Cases
But is all weather data created equal? The short answer is no. There is a matter of refinement, meteorological science, algorithms and knowledge that make all the difference when it comes to accuracy for both historical and predictive uses. Advanced technologies take multiple data sets and generate indices from them that communicate the impact of a weather peril. These analyzed insights combine historical, climatological and predictive technologies to produce actionable decision support before, during and after a major weather hazard. High resolution in the weather data along with street level or geocoded detail is key to accuracy.
In each stage of analyzing risk for the insurance company, sophisticated weather technologies combined with details on staffing, policyholder assets and past property impacts can inform numerous constituents in the process. While inaccuracies in weather reporting may translate to a minor inconvenience for the general public when a rainstorm unexpectedly occurs, the stakes for insurer accuracy are dramatically different. High-value weather data can bring clarity and insights to your decision-making to help you avoid costly impacts to your business.
Use Cases
Much is also changing in the ways insurers use weather data, including new products, like parametric insurance models, which automatically pay out immediately following a qualifying event. Combining contextual data with telematics-monitored driving behavior is yet another recent use case expanding the ability to better determine automotive risk.
Other newer uses include actionable alerts to relocate or protect property in advance of a dangerous storm. The key here is pinpoint accuracy to ensure responsiveness.
Some of the more traditional uses include
- Financial loss impact projections – post event for reserving and assessing probable exposure
- Resource deployment, pre- and post-weather event
- Underwriting: risk selection, risk scoring, geomapping for purposes of pricing, management of risk exposure
- Loss and claim investigation
- CAT modeling, e.g., hurricane, wildfire
- Enterprise risk management, portfolio perspectives
See also: Auto Claims and Collision Repair: The Great Reset
Winds of Change
Numerous recent developments have emerged to focus society in general, and the insurance industry specifically, on various aspects and applications of sophisticated weather technologies.
The ESG (environmental, social, and governance) movement is suddenly causing corporations to embrace long-term value creation, with its emphasis on stakeholders, society and sustainability, and has become a strategic imperative for insurance companies. Incorporating climate change and other potential disruptions into business models can help insurers drive long-term value for all constituents.
A wide variety of new and emerging technologies are enabling transformative improvement across the insurance enterprise, including product pricing, underwriting, distribution servicing and claims.Integrating hyper-local historic and real-time weather data into new solutions that leverage artificial intelligence and other high value third-party data is creating powerful capabilities in claims and risk scoring.
Driver safety solutions powered by contextual telematics, including weather and road conditions, is enabling new and important safe driving and travel features. New and exciting integrations of multiple data sources will continue to drive innovation in the insurance sector. Marrying this with greater weather data accuracy is the key to making these developments even better. And knowing which data and models produce the greatest accuracy is paramount to making these emerging and known uses cases optimal and actionable.
The P&C insurance industry, through collaboration with innovative data and weather scientists, has an opportunity to minimize the impact of changing weather conditions to the benefit of all stakeholders, including policyholders.
