CASE STUDY

Payer Insights

THE PROBLEM

"Payers struggled to assemble claims data, resulting in limited insights into network composition and leakages. These network leakages created cost burden and plan-holder churn within the payer network."

SOLUTION OUTCOME

25%

RETENTION INCREASED

Plan holder retention improved through targeted plan matching and network insights.

12-15 hrs

DAILY TIME RECOVERED

Manual data processing time was eliminated daily across at least three data team members.

Leakage Visibility

LEAKAGE INSIGHTS

Clear referral and competitor visibility helped payers reduce leakage risk.

Challenges holding Payer Insights back

Healthcare payers struggled to consolidate claims, referral, utilization, and network data, limiting visibility into plan performance, risk, and network leakage.

The Challenges

01Network Composition Blindness

Payers lacked visibility into network composition, limiting provider optimization and plan performance analysis.

02Referral Leakage Gap

Disconnected payer and provider workflows allowed referrals to move out of network, increasing avoidable costs.

03High-Risk Member Inaction

Payers could not identify high risk members early, delaying preventive care and increasing higher cost claims.

04Manual Data Processing Gap

Claims data was manually assembled and transformed, delaying insights and adding daily processing effort.

Challenges Impact

Network

LEAKAGE

Risk

BLIND SPOTS

Processing

EFFORT

  • Uncontrolled Network Leakage CostsReferrals flowing out of network without visibility created avoidable cost increases across thousands of claims.

  • Plan Holder Churn from Poor FitWithout proper plan differentiation, payers struggled to align plan holders with the right coverage, resulting in dissatisfaction, lower retention, and renewal losses.

  • High Risk Claims Left UnmanagedMembers with chronic and high risk conditions progressed without early engagement, increasing emergency and acute care costs.

  • Manual Data Processing OverheadData teams spent four to five hours daily assembling and transforming claims data manually, delaying downstream decisions.

  • Competitive Network ExposurePayers lacked visibility into competitor networks, weakening contracting decisions and increasing member migration risk.

Our Solution

Web-based Payer intelligence platform to transform claims
data into network and
utilization insights

A web based analytical platform that processed large volumes of payer claims data and delivered insights across network composition, utilization, high risk member tracking, and competitive benchmarking through automated workflows and structured dashboards.

Solution screenshot

Solution

Gave payers clear network composition metrics and coverage insights at physician and geography level.

Connected payers, providers, and plan holders through integrated referral workflows to close out of network leakage.

Tracked and flagged high risk members automatically for early preventive engagement.

Delivered year on year and month on month comparisons for contracting decisions, forecasting, and budget planning.

Solution Highlights

Network Coverage Reporting

Delivered payer coverage and formulary insights with physician and geography level drill downs for better network visibility.

Referral Workflow Integration

Connected payer, provider, and plan holder operations through shared referral workflows to reduce out of network leakage.

High-Risk Member Tracking

Tracked high risk members in real time to enable early preventive care engagement.

Step Therapy Decision Support

Enabled faster contracting and plan design decisions through granular step therapy analysis.

Forecasting and Budget Comparisons

Generated year wise and month wise comparisons to support forecasting and budget planning.

Automated Claims Data Pipeline

Replaced manual claims processing with automated pipelines delivering clean structured data for analysis.

Tech Stack

Azure

Azure

Power BI

Power BI

Functions

Functions

Data Lake

Data Lake

Blob Storage

Blob Storage

Python

Python

Spark

Spark

React

React

OUTCOMES & FEATURES

Improving payer network intelligence,
referral visibility, and plan performance

The platform helped payers move from fragmented claims data to a centralized analytics environment with better network visibility, referral tracking, risk monitoring, and faster planning decisions.

Key Outcomes

Improved Plan Holder Retention

Retention improved by 25% through better coverage matching using network composition insights.

Eliminated Processing Overhead

Automated claims pipelines eliminated four to five hours of manual daily data processing per team.

Faster Referral Response

Payers responded to referral gaps faster through real time visibility into out of network patterns.

Personalized Plan Delivery

Plan holders received coverage aligned to their health profiles through member analytics insights.

Proactive Risk Management

High risk members were identified and engaged early to reduce emergency and acute care escalation.

Competitive Network Positioning

Competitive benchmarking visibility supported stronger contracting and plan design decisions.

Features

Claims Analytics

Network Intelligence

Referral Leakage Tracking

High-Risk Member Monitoring

Utilization Analytics

Forecasting Intelligence

Power BI Dashboards

Our Engineering
Marvels
That Drive
Digital Transformation

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