Admiral Seguros, the Spanish arm of Admiral Group serving over 260,000 clients across three auto insurance brands, faced a claims handling process that had not kept pace with customer expectations. Appraisers manually reviewed vehicle damage images submitted by policyholders via email, producing estimates that were slow, inconsistent, and labor-intensive. With high daily claim volumes, the appraisal team was stretched thin — each case demanded individual attention regardless of complexity. In a market where speed and convenience increasingly define customer loyalty, this manual workflow created friction at exactly the moment policyholders were most vulnerable, eroding satisfaction and limiting the insurer's ability to scale efficiently.
Admiral Seguros partnered with Tractable to implement AI-powered visual damage assessment using computer vision, enabling a fully automated Straight-Through Processing (STP) workflow for auto claims. The integration works at First Notice of Loss: when a policyholder reports vehicle damage, Admiral Seguros's processing team sends them a link to a smartphone web app. The customer photographs the damage, and Tractable's computer vision model analyzes the images, identifies affected components, and automatically generates a repair cost estimate — without any appraiser involvement. Because the estimate is AI-generated and ready for review in minutes, the entire claims cycle from photo submission to settlement offer is completed digitally. The system integrates with Admiral Seguros's existing claims processing infrastructure, allowing the STP workflow to sit alongside human review for complex or edge-case claims.
In 2021, Admiral Seguros processed 12,000 touchless claims using Tractable AI, establishing a clear benchmark for what automated P&C claims handling can deliver at scale:
Customer adoption exceeded expectations across demographics — including an 84-year-old policyholder who called to praise the process — demonstrating that UX simplicity drives uptake regardless of age or digital familiarity.
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