Geocoding
Having an exact location is the foundation of cat analytics, directly affecting loss measures, underwriting, capital management, and reinsurance purchasing.
eBook: An Insurance Underwriters' Guide
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Purpose-built Geocoding Data
Chris Sams, Senior Product Manager, discusses the importance of purpose-built geocoding data.
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. Moody's RMS Geocoder delivers relevant, accurate risk management data for your needs.
Benefits
Know Where You’re Insuring
Moody's RMS curates the accurate sources of building perimeters, points of interest, land parcels, street networks, postal codes, administrative areas, and insurance market-defined boundaries to create the most fit-for-purpose insurance geospatial reference dataset for geocoding.
Manage Data on Poor Address Quality
The geographic centroid of a postcode is irrelevant for risk management purposes if there’s no exposure in its vicinity. Moody's RMS provides coordinates weighted to exposure density to ensure that you understand the best estimate of exposure on properties you underwrite when input addresses are of poor quality.
Understand the Impact of Changes
Every year administrative boundaries change, postal codes are updated/retired, new street networks are created, street names are changed, and territories are redrawn. Yet, many geocoders make these updates without concern to the end-user. Moody's RMS geospatial engineers provide detailed and thoughtful change management summaries to help you handle the impact of data changes.
Reduce Uncertainty
What if your geocoded locations are not as accurate as your match level states? False positives undermine your analytics and make inaccuracies harder to find and investigate. Moody's RMS geospatial models provide natively calculated “confidence scores” to help eliminate false positives and easily understand how the geocoder arrived at a particular match.
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 transformational phase where profit margins continue ...
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 and optimize capitalization. Detailed probabilisti...
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