Computer Vision Claims
AI-based image and video analysis that assesses property or vehicle damage, classifies loss severity, and estimates repair costs from photos.
technicalPublished 2026/06/07Last verified 2026/06/07
FAQs
- Can computer vision models handle all vehicle makes and models, including older or rare vehicles?
- Leading platforms are trained on tens of millions of damage images and cover the vast majority of vehicles in the US fleet. Accuracy may be lower for rare, vintage, or heavily modified vehicles, which typically require supplemental adjuster review. Carriers should request validation statistics segmented by vehicle type before deployment.
- How do we handle situations where a claimant submits photos that do not capture all the damage?
- Most platforms include image completeness scoring that prompts the claimant to submit additional angles or coverage before proceeding. For complex losses, the system routes to a virtual or field adjuster rather than issuing an automated estimate on incomplete evidence.
- Is a computer vision estimate defensible if a claimant disputes the repair cost?
- Yes, provided the estimate is generated by an auditable model with documented methodology and integrates with a recognized parts and labor pricing database. Carriers should maintain the image set and model version used for each estimate to support any dispute or litigation.
Related Terms
Claims Severity Model
A model predicting the ultimate cost of an individual claim, used to set reserves, prioritize handling, and flag high-exposure files.
SIU Referral
The process of routing a suspicious claim to the Special Investigations Unit for investigation of potential fraud before settlement.
Allocated Loss Adjustment Expense
Expenses directly attributable to a specific claim, such as attorney fees, independent adjuster fees, and expert witness costs.
Synthetic Data Insurance
Artificially generated data that replicates real insurance data distributions, used to train models when real data is scarce or privacy-restricted.