Enhancing Risk, Acreage & Claims Management

Context

This case study outlines detailed potential use cases where DigiFarm’s satellite-based field boundary and crop analytics solutions can support crop insurance operations. The aim is to highlight areas where DigiFarm’s core technologies enhance accuracy, efficiency, and decision-making in underwriting, claims management, and risk assessment, including estimated percentages of potential time and cost savings.

Core Technologies

• Field Boundary Detection: High-accuracy delineation of field boundaries using satellite imagery.

• Deep Resolution Imagery: AI-enhanced Sentinel-2 satellite imagery, improved from 10m to 1m per pixel.

• Dynamic Boundaries: Yearly and in-season field boundary updates to capture real-world changes.

• Crop Classification: Tailored models for specific crops, agro-climatic zones, and client requirements.

• Land Cover and Area Assessments: Classification of cropland, pasture, forest, and other land uses.

• Baseline Sustainability and Productivity Benchmarking: Relative average field productivity maps, comparing fields against regional benchmarks.

• Integration Options: RESTful APIs or customized dashboards for seamless integration and access.

Use Cases

1. Field Boundary Detection and Acreage Reporting

• Traditional datasets are often outdated; DigiFarm’s boundaries are generated dynamically for each growing season.

• Accuracy exceeds 98% when benchmarked against RTK boundaries, with regulatory acceptance in Europe.

• Supports precise acreage reporting, reducing disputes and re-checks.

Impact: Reduces manual boundary verification time by ~60–70%, lowering associated costs by ~30%.

2. In-Season Acreage and Productivity Assessment

• Detects planted acres vs. the full field area mid-season or the historical average

• Reflects real-time changes due to flooding, re-seeding, or abandonment.

• Enables early insurance adjustments without waiting for end-of-season.

Impact: Insurers can cut reporting delays by ~50%, leading to faster policy updates and ~20–30% reduction in claim investigation costs.

3. Damage Assessment and Claims Management

• Detects crop losses from hail, flooding, or drought within days.

• Provides precise damage mapping, limiting the need for on-site inspections.

• Cloud cover may delay assessment, but average confirmation is within ~7–15 days.

Impact: Ground inspection visits reduced by ~40–60%; claims processing time shortened by ~30–40%.

4. Crop Classification and Crop-Type Specific Models

• Identifies crops like corn, cereals, citrus, and tree crops.

• Models can be regionalized and season-adjusted, boosting accuracy.

• Useful for seed production monitoring and orchard management (e.g., detecting abandoned vs. productive orchards).

Impact: Classification automation reduces surveyor reliance by ~50%, and improves underwriting accuracy by ~15–20%.

5. Land Use / Land Cover Analytics

• Adds insights on cropland, pasture, forest, and non-productive land.

• Supports sustainability compliance and subsidy eligibility verification.

Impact: Reduces compliance checking time by ~40% and potential reporting disputes by ~20%.

6. Baseline Sustainability and Productivity Benchmarking

• Generates relative average field productivity maps, comparing fields against regional benchmarks, showing fields with increasing or decreasing productivity over the years

• Identifies improving, stable, or declining performance trends.

Impact: Enables insurers to segment risk more effectively, potentially reducing high-risk exposure by ~10–15% and offering targeted discounts that improve customer loyalty.

7. Integration and Delivery

• RESTful API for embedding into existing systems.

• Interactive dashboards or self-service portals as an alternative delivery.

Impact: Automates up to ~70% of manual data handling tasks, reducing IT integration workload by ~25%.

8. Collaboration and Customization

• Rapid iteration of models based on client needs.

• Proven ability to add features (e.g., solar panel detection) within short cycles.

Impact: Customization leads to ~20% faster deployment of client-specific solutions compared to off-the-shelf platforms.

——————————————————————————

Insurance-Specific Benefits

• Faster onboarding of insured farmers with prepopulated boundaries (time saved: ~50%).
  
  

• Improved underwriting accuracy with in-season acreage monitoring (cost reduction: ~15%).
  
  

• Early detection of crop damage for faster claims (processing time reduced by ~30%).
  
  

• Remote claims validation reduces inspection costs (~40–60% savings).
  
  

• Compliance with acreage reporting and subsidy requirements (time saved: ~40%).
  
  

• Enhanced risk pricing with productivity benchmarks (improves pricing accuracy by ~10–15%).
  
  

• Supports automation in workflows, lowering operational risks.

Time Sensitivities

• Satellite revisit: 2–3 days globally.
  
  

• Assessment window: ~7–15 days with cloud cover.
  
  

Impact: Near real-time monitoring reduces claims-related delays by ~25–35% compared to traditional methods.

Summary

DigiFarm’s technology is designed to complement, not replace, the work of insurance professionals. By automating routine tasks and delivering timely insights, it frees up experts to focus on higher-value activities such as complex assessments, customer engagement, and strategic decision-making.

DigiFarm provides insurance-grade, satellite-based analytics that improve underwriting, claims, and risk management.

With measurable time and cost savings (typically 20–60% across key workflows), insurers can streamline operations, lower costs, and deliver faster, more transparent services to growers. Scalable, affordable, and validated, DigiFarm’s solutions offer a strong foundation for modernizing crop insurance workflows.