Insurers Use Technology to Assess Climate Risk


Insurance companies continue to experience record losses from weather-related events. In addition to natural catastrophes such as hurricanes, floods, and earthquakes, there are secondary perils such as hail storms, tornadoes, thunderstorms, and wildfires that are causing more frequent and severe losses. Secondary perils are responsible for tens of billions of dollars in losses every year.

To help get a handle on climate risks, develop underwriting strategies and pricing, and reduce exposure, insurers are increasingly turning to new technology. Let’s take a look at some of the technology the industry is using.

  • In July, Aon announced a multi-year collaboration with Asia Pacific climate data and analytics provider AbsoluteClimo to help advance climate modeling and inform better decisions as organizations navigate emerging volatility from climate-based perils. Data provided by AbsoluteClimo’s proprietary global climate physics and catastrophe machine learning models, GoTCHA and ClimoCats, helps to inform Aon’s catastrophe modeling teams, allowing climate change considerations to be incorporated into modeled results for clients.
  • Two years ago, Swiss Re partnered with Finnish company Iceye Oy, a commercial radar satellite operator and flood monitoring provider, to leverage radar data that provides the reinsurer with quick and accurate flood-related information in order to monitor natural catastrophe events. Swiss Re’s proprietary intelligence tool, CatNet®, provides quick overviews and assessments of natural hazard exposures worldwide. It assesses the risk by combining hazard, loss, exposure, and insurance information with selected background maps and satellite imagery.
  • Zurich utilizes the power of artificial intelligence (AI) and machine learning in risk modeling. For example, the insurer is using AI neural networks to create global hazard maps for the current and future climate. The AI networks generate these hazard maps by combining data from climate models with current hazard maps.
  • Munich Re’s Location Risk Intelligence Platform is a comprehensive software solution to analyze and manage physical risks of natural hazards and climate change. It combines different assessment models to generate detailed assessments based on data from past events and future-oriented assessments that consider a wide range of internationally agreed climate change scenarios on the other. There are three editions: Natural Hazards, Climate Change, and Wildfire HD.

Tech companies continue to work on better and more accurate modeling for insurers, government entities, and the public. For example, Microsoft uses AI models to predict where the next blaze could be sparked. Microsoft’s team feeds its model with maps of previously burned areas, along with climate and geospatial data. The model can sift through historical weather and climate data to identify patterns, such as typically drier areas, and build a probability map of what has occurred in the past.

As climate-related risk becomes increasingly more challenging for insurers, investment in new technology and modeling platforms has accelerated to help with forecasting, mitigation, underwriting, and pricing.