In property insurance, precision in assessing risks is a prerequisite for pricing policies competitively and curtailing excessive claim pay-outs. With better location intelligence, carriers mitigate risks, accelerate claim procedures, improve fraud detection and expand their customer base. Location intelligence (LI) has become crucial to enabling organizations in several industries to achieve strategic business goals, with the LI global market expected to grow to $32.8 billion by 2027. Underpinned by geographic information systems (GIS), LI enables businesses to map, analyze and share locational data. In the case of parametric insurance, LI forms the core technology when environmental perils are trigger points.
Interestingly, carriers stand to gain across a variety of processes, ranging from managing policyholder addresses to providing property risk coverages to handling claims logistics. By overlaying and modelling historical claims with weather patterns, high exposure areas are predicted. Rich location data such as region-specific theft rates, hyper-local weather conditions provide valuable insights that aid product development, marketing and pricing models. LI also helps identify fraudulent claims.
Breakthroughs in open data, artificial intelligence, visualization and LI APIs have all paved the way for brisk uptake in LI solutions by insurers.
A substantial amount of environmental data is open. This makes possible easy access to rich data points such as weather data, earthquake reports and flood alerts, most of which is accessible through seamless APIs. Remarkably, satellite data has become much more affordable through sources such as Copernicus, NASA’s Global Flood Monitoring System and OpenQuake.
Location Intelligence APIs
Location Intelligence APIs integrate into existing workflows augmenting policy systems, underwriting and agency portals. The APIs expose key data and insights that aid risk assessment through several available data products and associated services. Cross functional teams share datasets to produce a consistent view of risk. RMS provides Location Intelligence APIs through cloud based Risk Intelligence, exposing geocoding services, hazard lookups and risk scores.
Geospatial data visualization tools such as Map View by LexisNexis, offer visibility into risks encompassing flood, windstorms, fire and crime spanning a carrier’s book to help price better, plan strategies for extreme weather events and manage claims. Carriers have reported 50% reduction in flood exposure and 8% improvement in new business.
AI/ML with location data
While non-AI prediction tools have existed for some time, AI enriches the process with more variables to make accurate predictions. One major insurer has used AI-driven methods to generate smart routes for drivers—turn-by-turn directions for the safest path to a destination. To generate this routing, the program considers many variables – accidents for different locations, the time of day and the weather – engendering fewer accidents and lower premiums.
With thousands of attributes augmenting location data sets, it gives fillip to new discovery of causalities and correlations. For properties located along a coastline that are subject to greater risk from severe weather events, an insurer can more effectively determine risks by assessing the distance between insured properties and the nearest coastline. Similarly, wildfire risk can be understood based on distance to combustible vegetation, wind patterns, the direction of nearby roads, roofing material and elevation. With regard to earthquakes, the damage from risk is better understood by analyzing soil density.
LI and Parametric Insurance
An insurtech specializing in index insurance, Skyline has developed a solution for renewable solar energy. By combining its index modelling strengths with big data geospatial solution ARLAS from partner Gisaïa, Skyline provides quick cash disbursement upon the occurrence of adverse events. Their risk transfer platform lets clients monitor and insure the lack of solar radiation. Other environmental parametric products deploy IoT sensors to record environmental conditions (e.g. flood water levels). Device availability and monitoring via LI technology has provided impetus to this growth.
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