Capco and Yarowa partner on AI-based insurance solutions
Announced on 27 November 2025, fintech Yarowa has teamed up with Capco to bring AI-driven workflows to insurance claims and third-party provider management. The partnership focuses on speeding up provider selection and improving document processing accuracy without adding overhead to claims teams.
Yarowa connects insurers and property managers with service providers across legal, health, property, craft, and automotive. In claims, the platform aggregates and standardizes information about specialists so carriers can find the right provider fast and with better oversight.
What the collaboration delivers
Capco's agent-based workflows help identify and select third-party providers quickly, while an orchestration layer coordinates the steps end-to-end. The stack runs on Microsoft Azure and its latest AI services, bringing scalability, security, and a clear path to integration with existing systems.
In practice, documents such as invoices are uploaded and processed by specialized agents and a central orchestrator that extract, classify, and verify key fields. A human-in-the-loop operator then approves the service provider and claim request or routes it for additional review. Reported outcomes include a reduction in human interactions by more than 90% and a smoother customer experience.
Yarowa's leadership highlights Capco's modular approach and speed, noting that co-development produced strong results in weeks. Capco points to accelerators from its AI Lab and emphasizes that the solution is built for both agile scale-ups and large enterprises.
Why this matters for insurance leaders
- Claims throughput: Faster intake, triage, and provider assignment without sacrificing control.
- Supplier due diligence: Consistent checks on provider credentials, pricing, and documentation.
- Operational cost: Lower manual effort on repetitive verification, freeing adjusters for higher-value work.
- Consistency and auditability: Centralized workflows with clear decision logs for compliance and QA.
- Time-to-value: Modular components shorten build cycles and reduce integration friction.
- Data governance: Azure-native services support enterprise-grade security and access controls.
For more on the platform foundation, see Microsoft's Azure AI Services overview.
How it works at a glance
- Ingest: Upload invoices and supporting documents.
- Understand: AI agents extract and normalize entities (provider details, amounts, dates, tax, line items).
- Verify: Cross-checks for completeness, pricing, policy constraints, and potential anomalies.
- Orchestrate: A central service sequences tasks, handles exceptions, and tracks state.
- Human-in-the-loop: Operators approve or escalate based on thresholds and flags.
- Decide and act: Provider is cleared or held; claim moves forward with an auditable trail.
Implementation checklist for carriers
- Start narrow: Pick one claim type with high document volume (e.g., property or motor).
- Define acceptance criteria: Accuracy targets for extraction, verification, and straight-through rates.
- Integrate via APIs: Claims, policy admin, supplier databases, and payments.
- Set clear thresholds: Decide which cases auto-approve vs. require human review.
- Track the right KPIs: Cycle time, cost per claim, exception rate, rework, leakage, and CSAT.
- Run a time-boxed pilot: 6-8 weeks to validate business impact, then scale.
- Align on governance: Access controls, PII handling, model monitoring, and audit requirements.
Skills and team readiness
Claims, SIU, and vendor management teams benefit from upskilling on AI-enabled workflows, exception handling, and data quality. If you're building capability internally, explore role-based learning paths here: AI courses by job.
The takeaway: this partnership packages AI agents, orchestration, and human oversight into a practical claims toolset. If your 2026 roadmap includes supplier vetting, invoice verification, or claims automation at scale, this is a blueprint worth evaluating.
Your membership also unlocks:
