Satellite Data and AI: The Shift to Data-Driven Agriculture Insurance
Crop damage due to flooding in the Upper Klamath National Wildlife Refuge in Oregon, captured June 25, 2020.
TechThe agricultural insurance market is in a critical period of evolution. With climate events increasing global crop exposure and operational costs rising, the industry is moving from traditional manual assessments to data-driven, scalable models. This necessary shift addresses a fundamental industry pain point: the scalability challenge in claims processing.
During our recent webinar, Agriculture Insurance Powered by Satellite Data: Insights for 2026, we were joined by industry leaders from NCIS, Swiss Re, AIAG, GreenTriangle, and PlanetWatchers to discuss how satellite technology, combined with artificial intelligence (AI), can automate and optimize claims workflows to help insurance companies save money and minimize risk.
The Challenge: Claims Scalability and Operational Bottlenecks
Crop insurers face massive operational bottlenecks during seasonal peaks, often needing to process thousands of field-level claims within very tight windows. This pressure leads to:
- Processing delays and high operational costs associated with deploying large field adjuster teams.
- Financial risk, such as being forced to pay a percentage of claims upfront just to manage the backlog.
- Lack of scalability of manual claim verification, a task that exceeds the capacity of even hundreds of loss adjusters.
The solution requires quality data and automated tools that drive immediate, quantifiable insights.
AI-Powered Validation: The Traffic Light System
The first step in achieving scale is the ability to triage all incoming claims automatically. Analytics assessing every claim can detect crop failure, parcel damage, or harvest events.
This capability is realized through an AI-powered process called Planet Area Monitoring Service (AMS) that applies a traffic light system to claims:
- Green claims: Analytics show no damage. These claims are flagged for potential secondary review or immediate closure, saving immense processing time.
- Red claims: Data confirms clear, verifiable damage. These can be fast-tracked for payment remotely, often validated in days instead of weeks.
- Yellow claims: These are the unclear or complex cases, and they are the only ones routed to expert adjusters.
This objective, auditable system provides transformative business impact by optimizing field resources and allowing adjusters to focus their expertise where it is truly needed.
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The Multi-Sensor Data Foundation
The engine behind this solution is Planet’s multi-sensor constellations, which provide the necessary combination of high-frequency monitoring and high-resolution detail:
- Go broad with monitoring: Near-daily 3 m resolution PlanetScope® imagery serves as the scalable engine for near-daily monitoring of hundreds of thousands of fields.
- Get close with tasking: When high-resolution detail is required, SkySat® and Pelican™ satellites can be tasked to provide 50 cm resolution imagery. This resolution can support processes like damage assessment, such as grading crop damage in bins of total, moderate, and low loss bins.
- Delve deep with analytics: Planet data and platform support advanced analysis for both risk assessment and claims, powering parametric products based on indices like Soil Water Content (SWC) and NDVI.
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Operating at Scale
The shift to data-driven processes is critical as the agro-insurance market grows, driven by the escalating challenges of climate change.
Use Case: Prevented Planting Claims
In the webinar, Tom Zacharias, President of NCIS, highlighted "prevented planting" claims as a primary candidate for satellite-driven efficiency. These claims pay farmers for failing to plant an insured crop by the final planting date due to an insured cause, such as flooding or drought, protecting against lost revenue and preventing equipment damage.
Zacharias went on to explain that during the 2019 season, prevented planting resulted in approximately $4.2 billion in indemnities and another $600 million in supplemental payments. Using objective satellite data to verify these claims improves program integrity, which is essential for maintaining trust in the public-private partnership between farmers, insurers, and taxpayers.
Scaling Through Solutions
The move to AI-powered satellite solutions is supported by collaborations across the industry, including:
- GreenTriangle uses satellite imagery to streamline loss assessment for many agriculture insurance firms, combining remote sensing with geotagged field data to generate instant, efficient expert reports.
- PlanetWatchers provides a focused solution for the US market, using AI and deep tech to merge optical and SAR data to identify sub-field planting activity and support underwriting, claims, and compliance.
- Swiss Re continues its long-term collaboration, confirming that remote sensing is expanding into underwriting and loss monitoring and that satellite data combined with AI is supporting faster, better insurance products overall.
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Ultimately, the foundation of modern crop insurance relies on trust in the system, and satellite technology plays an increasingly important role in providing that independent and auditable data source.
Ready to Scale Your Claims and Underwriting?
The most significant challenge in agriculture insurance, claims processing scalability, is being solved through the fusion of multi-sensor satellite data, AI-driven analytics, and platform automation.
Watch the full webinar recording to hear directly from industry leaders at Swiss Re, NCIS, AIAG, Green Triangle, and PlanetWatchers on their strategies for optimizing the insurance life cycle for 2026.
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