Computer Vision in Insurance

Computer vision in insurance automates the interpretation of visual data across the value chain. In claims, CV models analyze damage photos to estimate repair costs for vehicles, property, and equipment — generating estimates in seconds that match human appraiser accuracy. Aerial and satellite imagery analysis evaluates property conditions at scale: roof age and condition, vegetation proximity, flood zone exposure, swimming pools, and building characteristics.

Document OCR has evolved beyond simple text extraction: modern CV systems understand document layouts, identify relevant fields in context, and handle handwritten text. Identity verification uses facial recognition and document authentication to prevent application and claims fraud. The technology has reached production maturity: Tractable's damage assessment AI is used by 20+ insurers and body shops globally, Cape Analytics processes property imagery for major US carriers, and document processing platforms handle millions of insurance documents monthly.

The key enabler is training data — insurance-specific CV models require large, labeled datasets of damage photos, property images, and document types to achieve production-level accuracy.