Problem Statement

When calculating insurance premiums, insurance companies have traditionally relied on historical loss data, which may not accurately reflect current or future risk conditions. Underwriting is usually done at the beginning of the contractual relationship with periodic but limited updates. This reliance can result in premiums misaligned with the actual level of risk and its changes over time. Typically, insurers use generalized risk models based on broad assumptions and regional averages. These models often fail to account for the specific characteristics of individual properties or assets, leading to a uniform treatment of properties within the same region, regardless of factors such as elevation, proximity to natural hazards, or precise location. Traditionally, risk assessment and premium determination have involved manual inspections and on-the-ground surveys, which are labor-intensive and costly. Lastly, in dynamic environments where risks can change rapidly due to factors like climate change, natural disasters, or human activities, there is a growing need for insurers to adjust premiums dynamically in response to changing conditions. Continuous risk assessment is particularly well suited for construction sites, agricultural areas, or public infrastructures given the dynamic nature of building development, crop lifecycles, and the aging of roads and bridges.

How EO Helps

EO technology addresses these challenges by providing accurate, up-to-date, and location-specific data that can be used to enhance risk assessments and develop more precise, dynamic insurance premium models. By integrating satellite-derived information on hazards, exposure, and vulnerability, insurers can build dynamic models that reflect real-world risks and the corresponding changes over time. Optical and radar data offer insights into property conditions, vegetation health, and hazard history, while environmental variables like precipitation, temperature, and soil moisture inform predictive models for risk assessment. These technological shifts help insurers better understand and price risks, leading to more sustainable and equitable outcomes for both insurers and policyholders. Insurers can automate parts of the underwriting process by using EO data to quickly assess the risk profile of new policies. This reduces the need for manual inspections and speeds up policy issuance.

• Assessing Risk and Hazard Exposure: EO enables precise mapping of risks by providing detailed data on environmental conditions and historical hazard events. Optical imagery from satellites like Sentinel-2 and Landsat is used to assess property conditions, crop health, and proximity to hazard-prone areas. Synthetic Aperture Radar (SAR) data, such as that from Sentinel-1, complements optical imagery by detecting ground deformation, flood extents, or damage even under cloud cover. For climate-sensitive risks, EO-derived environmental data—such as precipitation patterns from GPM or temperature anomalies from ERA5—provides a historical baseline for hazard exposure and severity. These datasets feed into models that quantify risk probabilities and assign exposure ratings to insured properties or assets.

• Predicting Loss: EO supports dynamic modeling of vulnerability by analyzing site-specific characteristics and hazard intensity. In agriculture, indices such as the Normalized Difference Vegetation Index (NDVI) from MODIS or Sentinel-2 monitor crop health and drought impacts, enabling insurers to estimate potential yield losses. For property insurance, high-resolution optical and radar imagery helps identify vulnerabilities such as structural damage, proximity to erosion-prone coastlines, or wildfire risk. EO data also tracks long-term changes in vulnerability, such as the degradation of protective ecosystems like mangroves or wetlands, which can amplify disaster risks. Predictive loss modeling integrates EO data with ground-based information to simulate damage scenarios.

• Calculating Fair and Dynamic Premiums: The processed EO data can then be integrated into insurance risk models to calculate premiums more accurately and dynamically based on timely and historical risk profiles. In parametric insurance models, EO provides the trigger conditions for payouts, such as rainfall exceeding a predefined threshold or drought indices crossing a critical limit. This approach eliminates the need for costly on-ground assessments and speeds up claims processing. For traditional indemnity-based policies, EO data improves pricing precision by capturing variations in hazard exposure and vulnerability across insured assets. For example, radar and optical imagery combined with climate data can adjust premiums for properties based on their specific flood risk or fire susceptibility. Advanced analytics platforms process these datasets, enabling insurers to offer customized policies that reflect individual risk profiles.

• Verify Claims: After a natural disaster, EO data can be used to verify claims by comparing pre- and post-event imagery. This helps insurers quickly assess damage and process claims more efficiently, reducing the potential for fraud.



Case Study: AXA's EO-Enabled Drought Insurance

AXA, a global insurance leader, partnered with Planet, a provider of Earth Observation data, to create an innovative drought insurance program that uses high-resolution satellite data to monitor soil moisture, vegetation health, and drought intensity in real-time. AXA Climate receives detailed measurements of the volume of water contained in soil at a high resolution to a depth of about 5 centimeters in their areas of interest, which helps determine risk for drought-related losses, such as crop yields. This program offers a proactive insurance model that minimizes risk, provides timely financial relief, and enhances climate resilience for farmers by delivering accurate, localized data to optimize coverage and pricing decisions. The collaboration with Planet enables AXA Climate to dynamically update risk profiles, ensuring insurance policies remain relevant and responsive to environmental changes. This initiative not only strengthens AXA's market position and aligns with environmental sustainability goals but also demonstrates AXA's leadership in leveraging technology to manage climate risks and support broader climate change mitigation efforts.