Extract claimant information, loss details, policy references, and settlement amounts from insurance claim forms and supporting documentation—automatically.
Upload any document — PDF, scan, or photo — and get structured data back immediately. No setup, no templates, no waiting.
“After Hurricane season, we received 12,000 claims in a single week. Automated OCR let our intake team process the backlog in three days instead of the three weeks it took last year.”
“Our adjusters were spending 40 percent of their time on data entry. Now they spend that time actually evaluating claims, which improved both cycle time and customer satisfaction scores.”
“The accuracy on handwritten first notice of loss forms was better than we expected. Confidence scoring catches the edge cases so our team only reviews what needs reviewing.”
Audited controls over a sustained period, not a point-in-time check.
Bank-grade encryption at rest and TLS 1.2+ in transit.
Documents deleted within 24 hours. No copies retained.
Drag and drop files, connect a cloud drive, or set up email auto-forwarding. Any file format works—PDF, JPEG, PNG, TIFF, or digital documents.
The AI identifies fields by context and meaning, not fixed coordinates. Names, dates, amounts, and custom fields are extracted automatically.
Get structured output in Excel, Google Sheets, CSV, or JSON. Use the REST API for direct integration into your systems.
Insurance claims processing is one of the most document-intensive operations in the financial services industry. Every claim generates a file that includes the initial notice of loss, claim forms, police reports, medical records, repair estimates, invoices, and correspondence. Claims adjusters spend a significant portion of their time reading and re-keying data from these documents rather than evaluating claims and making decisions.
Insurance claim OCR addresses this bottleneck by automatically extracting structured data from claim documents. The AI reads claimant names, policy numbers, dates of loss, loss descriptions, damage amounts, and coverage determinations from forms that arrive in every conceivable format—handwritten first notice of loss forms, typed adjuster reports, scanned supporting documentation, and digital submissions. Unlike template-based systems that require configuration for each form type, AI-powered claim OCR identifies fields by context.
Speed matters in claims processing. Policyholders expect prompt resolution, regulators impose handling timelines, and carriers face reputational damage from slow claims. Lido processes claim documents in seconds rather than the minutes or hours required for manual data entry, enabling adjusters to focus on claim evaluation rather than administrative data capture. Batch processing handles catastrophe events when claim volumes spike dramatically.
Carriers and TPAs evaluating insurance claim OCR should consider accuracy across document quality levels, support for the full range of claim document types, integration with claims management systems, and security certifications. Lido provides field-level confidence scoring so uncertain extractions are flagged for adjuster review rather than silently accepted.
Insurance claim OCR handles first notice of loss forms, claim applications, adjuster reports, police reports, medical records, repair estimates, invoices, and general correspondence. The AI identifies the document type and extracts relevant fields automatically.
AI vision models read handwritten text on claim forms with high accuracy. Confidence scoring flags characters that may be uncertain, allowing adjusters to verify only the entries that need human review rather than re-checking everything.
Yes. Lido provides a REST API that returns structured JSON, which can feed directly into claims management platforms like Guidewire, Duck Creek, and Majesco. Excel and CSV exports are also available for systems that accept file-based imports.
Individual claim documents process in under five seconds. During catastrophe events when claim volumes spike, batch processing handles hundreds of documents in parallel so the intake process does not become a bottleneck.
AI-powered claim OCR typically achieves 95 to 99 percent accuracy on printed forms. Field-level confidence scores allow claims teams to set verification thresholds appropriate for financial data, ensuring that dollar amounts and policy numbers are correct before they enter downstream systems.
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Built on Lido’s OCR engine
Built on Lido’s OCR engine
Built on Lido’s OCR engine
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