The client is a leading American health solutions company that owns a retail pharmacy chain, a pharmacy benefit manager, and a health insurance provider, among other brands.
The company used to process and validate claims through their claims adjudication platform (PBM) but they wanted to migrate more customers to their own platform. However, different PBMs have distinct rules associated with different claims, causing challenges in onboarding new customers.
Our primary objective was to identify mismatches between two PBM platforms, detect defects and anomalies, and align the PBM rules to ensure optimized PBM migration. We leveraged an AI-driven system to streamline the manual testing process and successfully developed a certification testing solution utilizing Big Data implementation blended with Machine Learning (ML) to process records from both PBMs and run a hi-speed comparison algorithm to find mismatches.
Following were the notable business outcomes:
200% improvement realized in identifying clusters of similar-looking claims having issues
80% reduction realized in rework by the testing and operational resources
50% reduction realized in OPEX associated with the parallel testing process
AI helped create lean QA, with 60% cost reduction and improved accuracy
Improved testing effectiveness and accuracy
Reduced manual efforts through AI-driven system
Avoided redundancy and duplication due to manual efforts
Accurate predict requirements from claims
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