Why Open Geospatial Standards Matter in Regulated Insurance

Insurers rely on data from multiple systems and providers to assess property risk. Policy records, claims, building characteristics, hazard datasets, and catastrophe models all help insurers understand exposure across individual properties and entire portfolios.

Connecting these sources can be complex. Each new provider or application may introduce another interface to maintain, another dependency to manage, and additional integration work when systems change.

Open geospatial standards help insurers connect location data and services through established interfaces, making integrations easier to maintain and systems easier to extend. They do not eliminate integration complexity, but they give technology teams a common foundation for managing it.

Open geospatial standards

Open geospatial standards provide documented interfaces that compatible applications and services can use to exchange geographic information. Rather than relying exclusively on proprietary interfaces, insurers can use established specifications to connect geospatial capabilities across underwriting, portfolio analysis, and claims workflows.

Standards do not eliminate the need for integration. Data structures, security requirements, and application capabilities still need to align. However, they provide a more consistent starting point for connecting systems and evaluating alternatives.

Which geospatial standards matter?

The Open Geospatial Consortium (OGC) develops standards that support the exchange and use of geographic information. Three are particularly relevant to insurance applications.

• Web Map Service (WMS): Delivers georeferenced map images, allowing applications to display hazard layers without processing the underlying geographic data themselves.
• Web Feature Service (WFS): Provides access to geographic features and their attributes, supporting applications that need to retrieve and inspect spatial data.
• OGC API – Features: Defines modern web API interfaces for discovering and querying geographic features.

The right standard depends on the use case. Displaying a flood map is different from retrieving individual building footprints and their attributes for property-level risk assessment.

Supporting the same standard also does not guarantee seamless interoperability. Systems may use different data schemas, access controls, or interpretations of individual fields. Compatibility and data suitability still need to be assessed.

Four reasons open standards matter to insurers

Reuse geospatial services across workflows

Underwriting, portfolio analytics, and claims teams may all need access to the same property and hazard information. Maintaining separate integrations for each application creates duplication and additional operational work.

Open standards can help compatible applications reuse existing geospatial services, reducing the need to build every connection from scratch when introducing a new data source or analytical capability.

Improve traceability of risk assessments

For insurers, understanding a risk assessment can be as important as obtaining its result. Teams may need to establish which data informed a decision and how that data was processed.

Reproducing a flood risk assessment, for example, may require the original property data, the hazard dataset version, and the analytical method used. Standard interfaces can support data access, but they do not preserve this history on their own.

Traceability requires supporting controls such as metadata, data lineage, versioning, and appropriate logs. Open standards can contribute to the architecture, while the wider data governance and operational processes determine whether an assessment can be reproduced and reviewed.

Preserve flexibility as systems change

Replacing a data provider or analytical component can be costly when other applications depend on proprietary interfaces or data structures. The effort often extends beyond the replacement itself to rebuilding the connections around it.

Open standards provide a basis for evaluating alternatives and can reduce integration work when replacement systems support the required specifications and functionality.

They do not eliminate vendor dependency. Licensing terms, proprietary data models, and specialized features can still limit the available options. The objective is to avoid unnecessary dependencies and preserve flexibility where it matters.

Support different deployment environments

Insurers may operate geospatial services across public cloud, private cloud, hybrid, and on-premises environments. Standardized interfaces can help applications communicate across these environments, although moving services between them requires more than API compatibility.

Infrastructure, security, data residency, recovery arrangements, and operational responsibilities must also be considered.

This flexibility is relevant when insurers assess technology dependencies and third-party arrangements under the EU Digital Operational Resilience Act (DORA), which has applied since 17 January 2025. DORA establishes requirements for ICT risk management and operational resilience in the financial sector, including insurance; it does not mandate the adoption of open geospatial standards, though.

Bringing geospatial data into insurance workflows

Open geospatial standards give insurers a common foundation for connecting location data and services across applications. Their value becomes particularly clear when teams need to integrate a new data source, reuse an existing capability, or replace a system without rebuilding every connection around it.

Standards are only one part of the solution. Effective interoperability also depends on data quality, governance, security, infrastructure, and operational ownership.

Quarticle's cloud-native, API-first GeoIntelligence platform brings geospatial data, processing, analytics, and delivery together through interoperable services. For insurers, this provides a foundation for using location intelligence in property risk assessment, portfolio accumulation, and natural-event analysis.