Optimizing COPE insights with property intelligence
Jun 2025
Advanced property intelligence platforms like Nearmap offer portfolio-wide risk assessment capabilities, giving insurers a geographical overview of COPE data across all insured properties.
Jun 2025
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The COPE (Construction, Occupancy, Protection, and Exposure) framework equips underwriters with a comprehensive view of property risk by evaluating:
- Construction: Materials, design, and condition of a property.
- Occupancy: How a property is used and who occupies it.
- Protection: Resources or systems that minimize risks, such as fire hydrants or sprinklers.
- Exposure: External risks, including natural hazards or urban density.
Traditionally, gathering COPE data required time-intensive physical inspections and fragmented data sources. Today, property intelligence (the combination of aerial imagery and AI-derived insights) provides insurers with up-to-date, accurate information — streamlining the entire data collection process.
The power of property intelligence in COPE risk assessment
By leveraging AI and geospatial technology, insurers now have access to high-quality data that aligns with the COPE framework — a proven methodology for understanding and managing property risk.
Here’s how property intelligence turns COPE data into actionable insights.
Construction
Property intelligence allows insurers to evaluate structural details without site visits. AI models can detect:
- Roof attributes: Material (e.g., shingle, metal), condition (staining, damage), and geometry (hip, gable, or flat roofs).
- Building footprint and size: Verify square footage for accurate replacement cost assessments.
- Outbuildings or additions: Unpermitted structures, like sheds or garages, are identified — highlighting potential liability risks.
These insights ensure precise risk calculations, reduce underwriting errors, and lower costs associated with claims or premium leakage.
Occupancy
Intelligent property data simplifies determining how and by whom a property is occupied:
- Commercial vs. residential use: AI interprets zoning layouts, parking structures, and signage to distinguish between property types.
- Vacancy detection: Properties showing signs of neglect, like overgrown vegetation or boarded windows, are flagged as higher risk.
- Change detection: Track transitions over time, such as residential properties converted into short-term rentals.
This detail enables accurate pricing of policies based on current use as well as the potential risks of abandonment or tenancy changes.
Protection
AI data layers help insurers determine a property’s proximity to protective infrastructure:
- Defensible space for wildfire resilience: Analyze vegetation clearance and property layout.
- Fire station & hydrant proximity: Proximity to emergency services is key for determining response times and readiness.
- Access routes: Identify blocked or narrow driveways that may hinder emergency vehicles.
These insights provide a robust understanding of how well-protected a property is from perils like fire or severe weather.
Exposure
External hazards are critical in determining overall property risk. AI-driven geospatial tools offer insights on:
- Flood risk: Evaluate elevation data and mark signs of poor drainage.
- Wildfire zones: Identify nearby vegetation, slope, and urban-wildland interfaces.
- Hail and wind vulnerability: Assess geographic location and materials vulnerable to storm damage.
- Urban density risks: Detect property clustering for effective catastrophe modeling.
With exposure data integrated into risk scores, insurers can assess vulnerabilities comprehensively and mitigate claims proactively.
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Portfolio-wide risk insights
Advanced property intelligence platforms like Nearmap offer portfolio-wide risk assessment capabilities, giving insurers a geographical overview of COPE data across all insured properties.
Key benefits include:
- Identifying high-risk clusters: Highlight neighborhoods with at-risk features, such as aging roofs or flood-prone regions.
- Targeted market expansion: Spot low-risk, underinsured areas for profitable growth.
- Stress-testing resilience: Simulate how natural disasters, like windstorms, might impact entire portfolios.
By transitioning from property-specific insights to portfolio management, insurers gain a strategic advantage in optimizing risk distribution and identifying growth opportunities.
The competitive edge of collecting COPE data with property intelligence
Integrating aerial imagery and AI into COPE data collection allows insurers to enhance accuracy in underwriting decisions, expedite workflows, minimize costs, and improve customer satisfaction. It does this by automating insights, reducing premium variation and claims disputes, and replacing human error with tech precision.
Nearmap property intelligence aggregates up-to-date imagery and advanced AI insights to deliver actionable portfolio-level data for insurers. This powerful tool moves beyond individual property assessments, offering a clear view of risk distribution and portfolio quality metrics at a glance.
By quickly identifying COPE-related issues across thousands of locations, this geospatial approach empowers more strategic underwriting decisions — whether that be implementing moratoriums or adjusting rates. It also upgrades claims processing with benefits like faster settlements, lower adjusting costs, and a better customer experience.
Adopt property intelligence for your COPE data collection and realize its full potential.