The Gold Standard of Geospatial Property Intelligence Data

Crucial for precise risk assessment, informed underwriting, and effective claims management, geospatial property intelligence is foundational for property and casualty (P&C) insurance providers. Despite its importance, many insurers encounter challenges in sourcing and scaling high-precision data for geospatial analysis. 

In our recent webinar, Matthew Schmidt, Senior Associate on Ecopia AI’s (Ecopia’s) insurance team explores how innovations in artificial intelligence (AI)-based mapping are revolutionizing how both property and climate data are created and maintained, offering solutions to key challenges in the P&C insurance industry.

For those who missed the webinar, the recording is provided below. Additionally, this blog outlines the main takeaways from the webinar, giving you a glimpse into the key insights shared during the session.

Key challenges facing property & casualty insurance providers

Climate-related risks

According to the National Oceanic and Atmospheric Administration (NOAA), damages from climate disasters last year totaled more than $92 billion, marking the fourth consecutive year in which 18 or more separate billion-dollar disaster events impacted the US. As the webinar begins, Matthew acknowledges the growing impact of climate change on the P&C insurance industry. He highlights the significant risk to portfolios posed by the increase in frequency and intensity of climate events such as fires, tropical storms, and flooding. Extreme climate events such as these contribute to increased expenses throughout the insurance life cycle, impacting operational costs and claims losses. In fact, the impact is significant enough that some insurers have chosen to withdraw from states where the risk of severe climate events is particularly high. The ability to underwrite and reinsure in this changing environment is crucial to maintaining a competitive edge, and high-precision geospatial data plays a pivotal role in doing so.

Inaccurate geocodes   

For P&C insurers, the foundation of property intelligence lies in accurately representing the location of insured policies on a map. This process is achieved through geocoding. The ability for P&C insurers to determine the number and location of individual buildings at a given address is fundamental for policy underwriting, processing claims, and determining risk exposure. However, many geocoders fail to accurately identify the specific coordinates of a building associated with a policy. This is because the majority of geocoders use a parcel centroid approach, positioning a geocode at the central point of a land parcel even though a parcel may encompass hundreds of buildings, each potentially containing numerous addresses. Alternatively, geocoders might utilize street-level geocodes, which often approximate a building's location on a street rather than providing precise coordinates. 

Matthew demonstrates the inaccuracies associated with street level and parcel centroid geocodes by sharing an example of an address in rural Illinois, explaining that five separate geocoders produced drastically different results for the same address. One geocoder could not identify the address, while another misplaced it a mile away on the wrong road. The remaining three placed it within the correct parcel but in different locations, none of which accurately pinpointed the actual structure. Matthew explains the potential harm for insurers relying on inaccurate geocoding methods, including compromised risk assessments, miscalculated premiums, and difficulties in claims management.

Transforming P&C insurance with AI-powered building footprints  

Thankfully, advancements in artificial intelligence (AI) are helping to address the geocoding challenges facing P&C insurers. Building-based geocoding involves assigning geographic coordinates to specific building structures, enabling precise location identification for underwriting, claims, and more. Matthew explains that Ecopia’s AI-enabled technology ingests geospatial imagery to create high-precision building footprints and rooftop level geocodes. Ecopia’s AI-based mapping systems continuously ingest and process up-to-date geospatial imagery, empowering carriers to detect changes to structures like damage, additions, and other characteristics that impact a property’s risk profile. 

Matthew explains that building footprints can be appended with comprehensive address information as well as unique identifiers that facilitate the organization of associated attributes, including coverage amounts, inspection notes, and other relevant details for each structure on the property.

Ecopia provides a comprehensive view of the built environment giving insurers, like Openly, the high-precision data to make decisions. This lays the groundwork for crucial applications like policy underwriting, pricing, risk assessment, and more.

Policy underwriting

During the underwriting process, P&C carriers evaluate factors such as the property's location, construction material, occupancy, and relevant environmental conditions to determine the appropriate coverage, terms, and pricing for an insurance policy. AI-based building footprints and rooftop geocodes empower insurers with the high-precision data needed to assess risk associated with a policy, preventing carriers from relying on approximate locations to calculate risk.

Claims management 

AI-driven geospatial data is also instrumental in examining and handling claims within the realm of property and casualty (P&C) insurance. Location intelligence challenges stemming from inaccurate geocodes can impact property valuations and replacement cost estimates. This may lead to overpayment, posing financial risks for the provider. AI-based building footprints and rooftop geocodes give insurers the high-precision data they need to effectively assess and validate claims by accurately determining a property's location and assessing the impact on individual structures during an event. 

Master data management

Matthew emphasizes the importance for carriers to evaluate the quality of their geocoding systems and adjacent systems to ensure optimal location intelligence. He encourages carriers to consider exploring new products if the current system falls short in identifying each property to maintain competitiveness. He also highlights challenges in geospatial management within insurance companies, noting that geospatial tools often become isolated within specific business units, leading to inefficiencies, increased costs, and geospatial redundancy. 

Matthew explains that though P&C providers spend millions of dollars on geospatial-enabled systems or tools, many carriers lack a sustainable strategy for master data management (MDM) and struggle to create and maintain a unified database across their organization. He notes that insurers encounter MDM challenges with different departments managing various data sources. AI-powered building-based geocoding solutions provide unique identifiers for buildings, parcels, and addresses so all departments can develop a single source of truth to enhance efficiency and streamline operations.

Get started with AI-powered mapping to fuel insurance workflows

In a world marked by changing landscapes and complex addressing science, AI-based mapping is transforming how property intelligence data is created and maintained and can play an important role in mitigating some of the challenges facing the industry. The high-efficiency and cost-effective scalability of AI-based mapping make it easy to keep foundational property data up-to-date so insurers can maintain a firm-wide source of truth for analytics and decision-making in our rapidly changing world.

To learn more about Ecopia’s insurance solutions watch the webinar below and get in touch with a member of our insurance team.