Enhancing Healthcare Access & Revenue Visibility Through Insurance Analytics
Client
Health Trust, Nigeria
Sector
Health Tech
Geography
Nigeria, West Africa
Services
Data Engineering · Data Governance
Unified
End-to-end visibility into enrollment, claims, utilization and cost — one platform.
Platform Intelligence3 Risk Tiers
Predictive member segmentation — low, medium, and high-cost risk profiles.
Actuarial IntelligenceProactive
Shift from reactive claims management to predictive risk and pricing decisions.
Decision IntelligenceThe Client
HealthTrust HMO — expanding healthcare access across Nigeria
HealthTrust HMO is a fast-growing health insurance provider operating across Nigeria, working in alignment with the National Health Insurance Authority to expand coverage and improve healthcare affordability.
The organization partners with hospitals, employers, and government programs to deliver health insurance services to both formal and informal sector populations. As enrollment grew, the organization faced increasing complexity in managing claims, understanding customer behavior, and ensuring provider engagement.
The Challenge
Rising enrollment. No visibility into what it actually meant.
Despite rising enrollment numbers, actual healthcare utilization among insured members remained inconsistent. A significant portion of enrollees rarely accessed healthcare services, while others generated disproportionately high claims.
There was limited visibility into patient behavior, claims patterns, and regional disparities in insurance usage. Claims processing delays created friction between hospitals and the HMO, discouraging provider participation and affecting service quality. Additionally, revenue leakage and inefficient pricing structures made it difficult to maintain financial sustainability.
Predictive analytics and real-time reporting have transformed how we manage healthcare costs, improve provider oversight, and deliver better outcomes for our members.
The Goal
End-to-end visibility — from enrollment to cost, with predictive intelligence built in
The objective was to develop a centralized analytics solution that provides end-to-end visibility into insurance enrollment, claims activity, and healthcare utilization patterns.
The organization aimed to improve member engagement, optimize claims management, identify high-cost patient segments, and enhance provider performance monitoring. Additionally, leadership sought predictive insights to better forecast claims risk and design more sustainable insurance plans.
The Solution
A unified intelligence platform — from raw claims data to strategic decisions
A comprehensive Power BI dashboard was developed to integrate enrollment data, claims records, hospital billing data, and demographic information into a unified analytical platform.
Unified Analytics Platform
A consolidated data layer integrating enrollment, claims, billing, and demographic data. Real-time tracking of active enrollees, claims frequency, average cost per member, and provider performance — all in one live view.
Member Utilisation Intelligence
Interactive visualisations exposing disparities in insurance usage across regions, income groups, age bands, and demographic segments. Identifying who is underusing, who is overusing, and what patterns explain both.
Claims Efficiency Tracker
A dedicated claims performance module monitoring processing timelines, approval rates, rejection patterns, and delay hotspots across the provider network — giving operations teams the data to resolve friction before it damaged relationships.
Revenue Leakage Detection
Descriptive analytics surfacing patterns of inefficient billing, inconsistent pricing, and untracked cost exposure — enabling the finance team to identify and close revenue leakage that had previously been invisible and unquantified.
The Result
Faster cycles, better decisions, stronger provider relationships
The organization gained full visibility into the relationship between enrollment, utilization, and cost. Member engagement strategies improved as underutilizing segments were identified and targeted with awareness campaigns.
Claims processing efficiency increased, strengthening relationships with healthcare providers and improving service delivery. Predictive risk segmentation enabled better pricing strategies and reduced financial exposure from high-cost cases. Leadership transitioned to proactive decision making, improving both financial sustainability and healthcare access for members.
Leadership could now see, in a single view, exactly how premium income, member behaviour, and claims costs relate to one another — across any segment, region, or time period.
Underutilising segments — previously invisible — were identified, targeted with awareness campaigns, and brought back into active engagement with their coverage.
Faster, more consistent claims settlement made HealthTrust a more attractive partner for providers — improving both network quality and service delivery for members.
The actuarial risk tiers gave the product team a data foundation for designing insurance plans that were appropriately priced for each member cohort — reducing financial exposure from high-cost cases and improving the sustainability of the overall portfolio.
Unlocking previously unrecognised value that had been absorbed silently into the cost structure for years.
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