Geocoding
Having an exact location is the foundation of cat analytics, directly affecting loss measures, underwriting, capital management, and reinsurance purchasing.
Importance of Geocoding
The quality and accuracy of geocoding can make or break your model, especially when it comes to high-gradient perils such as flood, storm surge, and wildfire. A shift of a few feet can mean the difference between total loss or none at all. This makes geocoders purpose-built for insurance uses critical. RMS Geocoder delivers relevant, accurate risk management data for your needs.
Benefits
Global Dataset
RMS curates the most accurate sources of building perimeters, points of interest, land parcels, street networks, postcodes, and insurance market-defined boundaries to create the most innovative reference data. The result? Unsurpassed accuracy in your global geocoding process.
Exposure-Weighted Centroids
The exact geographic centroid of a postcode is irrelevant for risk management purposes if there’s no exposure in its vicinity. RMS provides coordinates weighted to exposure density to enable more accuracy in your analytics.
Ongoing Updates
Every year administrative boundaries change, postcodes are updated, street networks shift, and territories are redrawn. Yet, many geocoders make these updates without concern to the end user. RMS geospatial engineers provide detailed and thoughtful change management summaries to help you handle the impact of data changes.
Confidence Quantified
How do you know if a geocoded address is accurate? What if you’re modeling flood in an area where the street is long, the parcels are large, and the terrain is hilly? RMS models provide natively calculated “confidence areas” to quantify the uncertainty and enable sensitivity testing.
Resources
The Data Difference
The value of data as a driver of business decisions has grown exponentially as the importance of generating sustainable underwriting profit becomes the primary focus for companies in response to recent diminished investment yields. Increased risk selection scrutiny is more important than ever to maintain underwriting margins. High-caliber, insightful risk data is critical for the data analytics that support each risk decision The insurance industry is in a…
Underwriting With 20:20 Vision
Risk data delivered to underwriting platforms via application programming interfaces (API) is bringing granular exposure information and model insights to high-volume risks The insurance industry boasts some of the most sophisticated modeling capabilities in the world. And yet the average property underwriter does not have access to the kind of predictive tools that carriers use at a portfolio level to manage risk aggregation, streamline reinsurance buying…
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