Turn insurance documents into review-ready work
Extract policy, coverage, loss, and claim details from the documents in a case, then turn them into a professional deliverable your team can review and reuse.
No signup needed · 1,800 free credits
Insurance teams need more than extracted fields
- Critical details are buried in mixed files. A submission or claim can combine ACORD forms, policies, certificates, loss runs, spreadsheets, emails, and scans.
- Raw data still needs professional context. Underwriters, adjusters, and compliance teams need a usable intake, comparison, brief, or case summary—not another field table to rework.
- Review must stay traceable. Low-confidence fields, material gaps, and judgment-heavy decisions need an explicit human check against the source documents.
Insurance documents in, review-ready deliverable out
Bring the case documents together
Add submissions, policies, certificates of insurance, loss runs, schedules of values, endorsements, claim forms, and supporting emails or scans.
Define the fields and deliverable
Specify the policy, coverage, limit, loss, date, and evidence details to capture, plus the output your team needs next.
Extract and connect information
Kuse identifies document types, extracts relevant details, compares information across files, and flags missing or inconsistent evidence.
Review and reuse the output
Receive a source-grounded intake, comparison, compliance brief, loss summary, or case summary. Qualified professionals review material findings, then reuse the workflow for the next case.
Kuse Workflows
From document fields to work your insurance team can use.
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Automated Document Extraction for Insurance
01
What is automated document extraction in insurance?
Automated document extraction in insurance uses OCR and AI to read documents, identify relevant fields, and turn them into structured information without manual re-keying. It can work across semi-structured and unstructured files including PDFs, emails, spreadsheets, scanned forms, and handwritten notes.
02
Extraction is the input, not the final deliverable
OCR makes a scan machine-readable. Document extraction adds context by identifying file types, locating needed fields, and checking values against expected formats. But an insurance professional usually needs more than a data table.
Kuse keeps the source documents in context and turns extracted information into a completed underwriting intake, coverage comparison, compliance brief, loss summary, or review-ready case summary. For the broader workflow that also classifies, compares, generates, and routes work, see insurance document automation.
03
Which insurance documents can be extracted?
- ACORD forms and broker submissions
- Certificates of Insurance and endorsements
- Policies, schedules of values, and coverage documents
- Loss runs, FNOL forms, claim files, and adjuster notes
- Renewal documents, emails, spreadsheets, and scans
- Medical records for health insurance cases
04
What can Kuse deliver from extracted insurance data?
- Submission and attachment → pre-filled underwriting intake
- Multiple certificates of insurance → compliance brief with expiry and coverage-gap flags
- Loss runs → normalized loss summary with trends
- Expiring and renewal policies → comparison with material changes highlighted
- Medical records and a claim file → review-ready case summary
05
How to keep insurance document extraction reliable
Start with a clearly defined output and the fields that matter to it. Ask the workflow to flag missing evidence, conflicting values, and low-confidence extraction. Review material coverage, claim, compliance, and exception decisions against the supporting documents; automation reduces repetitive preparation work but does not replace qualified professional judgment.
06
Why reusable extraction workflows matter
Once a team defines the documents, fields, checks, and deliverable for a recurring process, it can reuse that workflow across similar submissions, claims, and renewals. The project retains its source context, and the workflow becomes a repeatable professional process instead of a one-time prompt.
07
Frequently asked questions
What is automated document extraction in insurance?
It uses OCR and AI to read insurance documents, locate relevant fields, validate them, and turn them into structured information. Kuse can then turn that information into a review-ready professional deliverable.
How is insurance document extraction different from OCR?
OCR makes text machine-readable. Extraction identifies document types and relevant fields. Kuse goes further by connecting information across the source package and producing a usable intake, comparison, brief, or case summary.
Can AI extract data from scanned insurance documents?
AI can help process scans, PDFs, forms, spreadsheets, and other document formats. Teams should set review rules for incomplete, ambiguous, or low-confidence information before it informs a material decision.
Can a workflow be reused for renewals and claims?
Yes. Define the documents, fields, checks, and target deliverable once, then reuse the workflow for similar cases while keeping human review where judgment matters.
Related Use Cases
Automate insurance documents across operations
See use caseCheck policies, renewals, and servicing work
See use caseStructure extracted document data
See use caseTurn insurance summaries into shareable pages
See use caseFormat insurance documents consistently
See use caseAutomate repetitive insurance tasks
See use caseTurn insurance documents into reusable professional work.
Extract the details that matter, produce a review-ready deliverable, and reuse the workflow for the next case.