Weather Analytics – New Opportunities for Insurance Industry


A one-third of U.S. economy is sensitive to the climate and weather. Insurance companies are now in the breakthrough to use the climate data to analyze the pattern of weather in real-time to track the impact on its cusomers. What if your insurance company could text you a warning before hail hits your area? Insurance companies stand to benefit from claims avoidance initiatives by providing climate and weather alert data in more real-time to their insured. The most obvious of these use-cases is the ability to share road condition data to drivers of personal and commercial vehicles. Every year, thousands of property claims are filed due to weather damages. Businesses lose $500 billion every year in the U.S. because of weather.Energy and utility companies say weather causes 70% of power outages. Insurance companies have always looked at weather patterns to determine whether to cover individuals and businesses. But in a time when it appears climate change may be contributing to an increase in natural disasters, these companies are now turning to weather analytics firms for greater insight and reduced risk. Internet of Things solutions, and the improved data analytics gleaned from them, can lead to business improvements and better subscription protection for insurers across all lines of insurance. The insurance industry is being called out by an international research institution for its progressive attitude on climate change.

Many P&C insurers are using external data sources to shift from a reactive model to a proactive model by investing in real-time risk and yield management. Insureres are looking at the use of telematics and real-time sensor data and embed these data within their operations and work flows to help manage their business, more effectively underwrite risk, compress time lags, and reduce claims activity/processing. Personal line insurance companies have the opportunity to factor-in possible road conditions when pricing policies for their customers. They can also use this data to examine road conditions when a vehicular accident claim is made Commercial lines insurers can use these solutions to better comprehend the statistical net effect of solar radiation and ionization conditions on electrical equipment failure when underwriting business property insurance.By having GPS data coupled with better knowledge of road conditions, drivers can be more careful behind the wheels. Vehicle operators supplied with better data are better able to avoid vehicular accidents. This is a great example of how real-time climate analytics — powered by connected IoT technologies — can improve the way insurers do business.

Another interesting application of an innovative business model is in the area of crop insurance. The Climate Corporation is taking publicly available data sources (satellite imagery, precipitation and soil maps) and modeling a field’s crop yield, essentially turning an insurance product into a loss control product

As per PWC, an increasingly useful 3 party data source is “macro” environmental information such as geocoding, satellite imagery, census, building code, natural catastrophe, environmental and climate data. When integrated with a carrier’s own data (such as risk penetration and geographic footprint), the resulting insights can proactively identify significant existing or potential risk concentration threats, and support a portfolio management approach to managing risk and profitability. These insights may be less obvious at the individual transaction level, but can help to uncover deep and potentially destabilizing ripple effects well ahead of an actual loss event

IBM and The Weather Company, including its global B2B division WSI, have formed a ground breaking global strategic alliance to integrate real-time weather insights into business to improve operational performance and decision making. Until recently, insurance companies didn’t have easy access to real-time weather data required to study climate effect and analyze ways to protect customers and better manage risk. Insurers relied mostly on historical weather data to determine if climate and weather patterns can increase insurance claims. Weather is perhaps the single largest external swing factor in business performance – responsible for nearly half a trillion dollars in economic impact in the U.S. alone each year. By combining IBM’s cloud computing, industry consulting and analytics expertise with precision weather data and forecasts, IBM and The Weather Company alliance can help enterprises across industries understand the impact of weather on their business and take action. IBM and The Weather Company alliance will jointly develop industry solutions, including insurance, energy & utilities, retail and logistics. Because of the partnership between IBM Research – India and UBD, Brunei is the first nation in the world to have a national-scale, high-resolution, integrated natural resources models which can be accessed by ordinary people and workers via tablet and smart phone interfaces. In addition, by working with IBM, Universiti Brunei Darussalam (UBD is able to distinguish itself as a top university.

Research firm Deloitte used government weather data in its report, “The Potential for Flood Insurance Privatization in the United States.” The study, which analyzed the risk of covering Americans for floods, shows whether or not insurers should pursue the flood insurance market. The data and analytics in the report, which show the positives and negatives of flood coverage, allow insurers to make their own decisions when it comes to providing premiums. Deloitte came up with its findings through information from FEMA, public sources and private insurers. The Deloitte report, for example, found that over the course of its history, the National Flood Insurance Program, which covers people affected by flooding, has “collected more in premiums than it paid out it claims.” However, certain storms, like Hurricanes Sandy and Katrina, resulted in losses for the public insurance program

Data Sources:

The ability to gather and hone climate data for practical purposes has been an incremental process. Traditionally, weather data was made available in aggregate through subscriptions to weather services. This information was infrequently updated on an expeditious basis, which made it difficult for insurers to use the data for policy pricing, underwriting or claims, or to provide additional information to subscribers so they are better prepared to deal with inclement weather and other adverse conditions.

  • The primary source for historical weather data is the U.S. National Climatic Data Center (NCDC) in Asheville, NC: http://www.ncdc.noaa.gov/. NCDC can provide hourly historical data for thousands of locations around the world. This data may not always be complete; data items or periods of record may be missing
  • A highly reliable source of historical data for U.S. locations is the Solar and Meteorological Surface Observational Network (SAMSON) data set assembled by the National Renewable Energy Laboratory (NREL) in Golden, CO: http://www.nrel.gov/. The SAMSON data set contains a 30 year (1961 to 1990) period of record for 239 locations and are available from the NCDC.
  • The TMY2 are data sets of hourly values of solar radiation and meteorological elements for a 1-year period. Their intended use is for computer simulations of solar energy conversion systems and building systems to facilitate performance comparisons of different system types, configurations, and locations in the United States and its territories. Because they represent typical rather than extreme conditions, they are not suited for designing systems to meet the worst-case conditions occurring at a location. The data are available from the National Renewable Energy Laboratory for download or on CD.
  • The Solar and Wind Energy Resource Assessment (SWERA) project, funded by the United Nations Environment Program, is developing high quality information on solar and wind energy resources in 14 developing countries. Currently typical year hourly data are available for 156 locations in Belize, Brazil, China, Cuba, El Salvador, Ethiopia, Ghana, Guatemala, Honduras, Kenya, Maldives, Nicaragua, and Sri Lanka. The data are available from the SWERA project web site. http://swera.unep.net/
  • Real-Time weather data is available from the EnergyPlus web site. From the web site: “Hourly weather data from stations across the world is continuously collected and stored into a local database. The data is available through this web interface. Most stations have information for dry bulb temperature, wet bulb temperature, wind speed/direction, atmospheric pressure, visibility, cloud conditions, and precipitation type. Data may not be available for all stations and may not be contiguous for time period selected.” The data is available in two output formats: CSV and IWEC

There is so much that depends on the weather, from outdoor concerts, sporting events, travel, wildfire potential all the way to seasonal crop yields. We are still very much dependent on the weather, and by most estimates and research, our global weather is becoming more extreme and violent. This is why the partnership between IBM and the Weather Channel announced earlier this year is so critical and offers so much potential to innovate. To help address the big data challenges of climate science, the Computational and Information Sciences and Technology Office (CISTO) at NASA’s Goddard Space Flight Center is developing a Climate Analytics-as-a-Service (CAaaS) capability. CAaaS is a specialization and extension of the Software-as-a-Service (SaaS) concept enabled by cloud computing. So while we’re not able to control the weather, better forecasting will allow us to make more informed plans that can limit financial losses, provide new business opportunities, reduce government spending, and even save lives.

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