COPE data are the building blocks of underwriting and managing portfolio risk for the Insurance industry. Information about the makeup of properties, what types of businesses occupy them, and what exterior hazards impact each, are necessary to accurately rate the risks. BFUSA links all of these critical elements to individual building level accuracy. Completeness and quality of data are our priorities.
Over 150 variables such as Construction Type, Year Built, and Square Footage, from our data curation of building structures, assessor/real property, building permit and other sources. Clients are using the data to augment SOV’s where information is missing or unreliable. Additionally, use the data to prefill the underwriting workflow.
BFUSA is able to identify if a building structure is residential or commercial. We have data available for over 16-million businesses nationwide. Understand the type of business for each by SIC or NAICs codes, as well as other details such as hours of operation, number of employees, estimated revenue, primary contacts, number of businesses per building, and more.
Use building footprint data to ask key questions related to structure protection that informs risk analyses and decisions:
- Distance to fire stations and hydrants
- Proximity to city/town infrastructure and services
- Types of structures that surround or are nearest to a specific building
- Identification of multi-family residential, apartments/condos and commercial structures
Man-made and natural hazards have an effect on each property. BFUSA collects key ground elevation data about each structure (min/max/average, building vertices) and first floor elevation. We have lists of hundreds of historical, modeled and predictive data elements that cover earthquakes, hurricanes, flood, wildfire, hail and many others. Combined with the precision of our building footprints, you are able to do hyper-accurate risk analysis.
The Problem With Poor Quality COPE Data
Client submitted SOV’s are inherently unreliable – incomplete addressing, primary and secondary building attributes are sparsely populated and have questionable quality
Fill rates from current 3rd party COPE data providers are often poor, resulting in low confidence for use in an underwriting process/decision
Heavy reliance on physical inspections/surveys that are costly and not scalable
Under/overstated impact on Cat and loss estimates
Individual data components are available, but not delivered as data solutions