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📸 '''Photo estimating''' is a [[Definition:Claims management | claims handling]] technique in which [[Definition:Insurance carrier | insurers]] assess property or vehicle damage using photographs submitted by the [[Definition:Claimant | claimant]] or captured by a field representative, rather than requiring a physical, in-person inspection. Originally adopted in [[Definition:Auto insurance | auto insurance]] to expedite minor damage appraisals, the practice has expanded into [[Definition:Property insurance | property insurance]] and other lines where visual documentation can substitute for — or supplement — a traditional [[Definition:Adjuster | adjuster]] visit. The approach gained significant momentum as smartphone cameras improved and [[Definition:Insurtech | insurtech]] platforms made it feasible to guide policyholders through structured, high-quality image capture.

🔧 In a typical workflow, the insured receives instructions — often through a mobile app or web portal — to photograph the damaged area from specified angles and distances. These images are uploaded to the insurer's [[Definition:Claims management system | claims platform]], where they are reviewed by a staff or independent appraiser, sometimes augmented by [[Definition:Artificial intelligence (AI) | artificial intelligence]] models trained to identify damage severity and estimate repair costs against standardized parts-and-labor databases. For auto claims, the estimate may be generated algorithmically and then validated by a human, allowing the insurer to issue a [[Definition:Claims payment | settlement]] within hours rather than days. In property lines, photo estimating may be paired with [[Definition:Aerial imagery | aerial imagery]] or [[Definition:Drone | drone]] surveys for roof and structural assessments, particularly after large-scale [[Definition:Catastrophe | catastrophe]] events when deploying adjusters to every affected property is logistically impractical.

⏱️ Speed and cost efficiency are the most immediate advantages — photo estimating reduces [[Definition:Loss adjustment expense (LAE) | loss adjustment expenses]], shortens [[Definition:Cycle time | cycle times]], and improves the [[Definition:Policyholder | policyholder]] experience by eliminating scheduling delays. For insurers managing high-volume [[Definition:Catastrophe claim | catastrophe surges]], the ability to triage and resolve straightforward claims remotely frees field resources for complex or high-severity losses. However, the technique carries limitations: photographs may not reveal hidden damage, and reliance on policyholder-submitted images introduces variability in quality and completeness. Fraud detection also requires additional controls, such as metadata verification and image authenticity checks. Markets across North America, Europe, and parts of Asia-Pacific have embraced photo estimating at varying rates, often influenced by regulatory expectations around inspection standards and consumer protection requirements in claims settlement.

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Claims management]]
* [[Definition:Loss adjustment expense (LAE)]]
* [[Definition:Artificial intelligence (AI)]]
* [[Definition:Adjuster]]
* [[Definition:Straight-through processing (STP)]]
* [[Definition:Virtual inspection]]
{{Div col end}}

Definition:Photo estimating - Revision history

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