AI for Insurance Underwriting & Claims
Read submissions, loss runs, and policy wordings faster. Extract structured data with source links and an audit log, for your own reviewers.
Built for
Why Insurance teams struggle today
The problems we see in every insurance workflow.
- Policy review for coverage gaps and exclusions takes underwriters hours per submission
- Claims documentation extraction is manual and error-prone under volume
- Underwriting risk assessments depend on unstructured broker notes and reports
- Reinsurance treaty analysis requires lawyer-level review of dense legal text
- Audit trail requirements add hours to every claim decision
How DataStruct AI solves it
Purpose-built capabilities for insurance workflows.
- Policy term extraction with coverage limit and exclusion mapping
- Claims evidence extraction with structured output and review routing
- Broker submission analysis (loss runs, surveys, financial statements)
- Risk language detection and exception flagging across document sets
- Regulatory compliance rule packs with source-linked evidence trails
Insurance use cases
The most impactful workflows DataStruct AI powers for insurance teams.
Underwriting Automation
Problem: Underwriters spend hours per submission reading broker packs, loss runs, and risk surveys.
Solution: Extract risk indicators, financial metrics, and key exposures with confidence scores and source links.
Impact: Underwriters focus on judgment calls, not data entry.
Claims Processing
Problem: Claims teams drown in adjuster reports, correspondence, and FNOLs with tight deadlines.
Solution: Extract claim facts and coverage terms with source links, and route items to a reviewer for decision.
Impact: Faster reviewer decisions from source-linked facts.
Reinsurance Treaty Analysis
Problem: Treaty wordings are dense legal documents; extracting recoverable terms across treaties is painful.
Solution: Clause and obligation extraction across treaties, each linked to its source, for side-by-side review.
Impact: Recover what you're owed. Spot adverse term changes at renewal.
Regulatory Reporting
Problem: Solvency II, NAIC, and PRA reporting requires traceable evidence for every disclosure.
Solution: Metrics link back to the cited source documents, with timestamps, for human review.
Impact: Assemble the evidence your reviewers need without the fire drill.
Document types we handle
Questions you can ask
- ›“What exclusions apply to this policy?”
- ›“Extract all coverage limits and sub-limits”
- ›“Compare deductible structures across the portfolio”
- ›“Identify subrogation provisions”
- ›“Summarise claims history from this loss run”
Why Insurance teams choose DataStruct AI
Evidence-cited AI
Answers cite the sources they rely on, and records the system could not confirm are shown separately for a reviewer to check.
Access control and audit
Workspace roles with granular permissions and an audit log on sensitive actions. Tenant isolation is enforced in the application layer.
11 industries
Pre-configured terminology, document types, and rule packs for your vertical.
See DataStruct AI in action
Tell us about your team, document volumes, and integrations. We'll put together a tailored package and walk you through the platform.