Real-time anomaly detection across pharmacy claims to flag fraud before payout
— Pharmacy Benefit Management
Solving: Pharmacy claims fraud patterns going unnoticed until after reimbursement
Machine Learning Architecture
Real-time anomaly detection across pharmacy claims to flag fraud before payout
Python, Kafka, PostgreSQL
Validated Business Impact
Improves fraud waste and abuse detection accuracy by 37%
Technical FAQ
How does JSRRB Technologies solve pharmacy claims fraud patterns going unnoticed until after reimbursement?
We deploy real-time anomaly detection across pharmacy claims to flag fraud before payout. Typical result: improves fraud waste and abuse detection accuracy by 37%.
What technology and security model powers this Pharmacy Benefit Management solution?
The solution is engineered on Python, Kafka, PostgreSQL, deployed under JSRRB's zero-trust architecture so your proprietary Pharmacy Benefit Management systems and data stay encrypted and are never exposed to public AI training models.