Case Study

Leading health insurer accelerates enrollment document processing with AI-powered automation

Industry

Healthcare and Life Sciences, Healthcare Payer

Location

USA

Our Contributions

AI/ML, Gen AI, Business Process Optimization

A major US health insurer was struggling to efficiently create benefit documents for millions of members across multiple states. They needed a strategic partner to streamline document workflows and ensure compliance, so they turned to Coforge for help reinventing the process with AI.

Transformation Timeline

Phase 1

Process assessment and end-to-end workflow design.

Phase 2

GenAI technology enablement and workflow platform integration.

Phase 3

Quality framework rollout, team onboarding, and full ownership of work queues.

Phase 4

Continuous governance, optimization, and peak-period scalability.

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The Challenge

The client was manually creating benefit booklets and Summary of Benefits and Coverage (SBC) documents for its members. With hundreds of templates for different states and employer groups, this manual process was making the enrollment cycle inefficient and prone to errors.

Creating the booklets had a steep learning curve. It required experienced staff to manually extract data from multiple unstructured document formats, a slow, resource-intensive process that could not be scaled during peak enrollment periods.

Human errors and inconsistent validation also created a very real risk of falling out of compliance with regulators.

Our Approach

Coforge built and deployed an AI-powered document automation solution designed to accelerate benefit booklet processing and improve compliance. Built on the Quasar AI platform, the solution leveraged automation and AI-enabled features to accelerate the process and improve quality.

Gen AI-Powered Entity Extraction Template Recognition

LLMs were trained to ingest, interpret, and extract the relevant data, then select the right document template for healthcare plan types like PPO, HMO, or HSA.

AI-driven ETL Workflows

AI agents were responsible for structuring and validating benefit data for members.

Human-in-the-Loop (HITL) Model

Instead of executing highly repetitive tasks, human efforts were saved for refining the final documents and ensuring high quality output.

Automated Compliance Checks

Each document was validated for alignment with CMS and state regulations before delivery.

CMS Integration

The solution was integrated with the client’s existing content management systems to enable seamless downstream processing.

Impact to Date

By using AI-powered extraction and validation, the solution significantly reduced manual effort, while incorporating feedback from underwriters and compliance officers to continually improve model accuracy.

75%

Reduction in Processing Time

95%

Accuracy in Data Extraction

100%

Compliance with CMS and State Regulations Shape