Insurance Claims Triage

Reduced claims processing time by 70% using an AI agent integrated with legacy core systems

Executive Summary

A large insurance provider aimed to modernize its claims triage process, which was heavily dependent on legacy mainframe systems and manual review. We deployed an AI-powered triage agent that seamlessly integrated with their existing infrastructure and automated first-level claims processing, drastically reducing turnaround time and operational overhead.

Challenge

Manual triage process causing significant delays
High variability and errors in claim categorization
Legacy systems not built for real-time integrations
Rising operational costs with increasing claim volumes

Solution

1. AI-Powered Triage Engine

Deployed custom NLP models to auto-classify incoming claims
Enabled confidence scoring and edge-case routing to human reviewers

2. Seamless Legacy Integration

Integrated AI agent with mainframe systems using secure adapters
Minimal disruption to existing workflows or training needs

3. Real-Time Dashboarding

Claims insights visualized in dashboards built with Power BI
Live feedback loop integrated for continuous model training

4. Deployment & Governance

Deployed in a HIPAA-compliant environment with full audit trail
Collaborated with legal and risk teams for compliance

Results

Impact Area	Outcome
Processing Time	Reduced average triage time by 70%
Claim Accuracy	Improved classification precision to 93%
Manual Review	Cut first-level human review by 80%
IT Overhead	Minimal system changes; no replatforming needed
Business ROI	Savings projected at $2.5M annually

Technologies Used

Python · FastAPI · PostgreSQL · Power BI · NLP Models · Mainframe Connectors · Azure Cloud · CI/CD · HIPAA Compliance Tools

Business Takeaway

The AI triage system delivered measurable operational efficiency and accuracy without requiring a complete technology overhaul. It set a precedent for future AI-led automation initiatives within the enterprise, while meeting stringent compliance needs.