The WhiteHatAI Centaur system is a flexible, patent-pending automated healthcare fraud detection software platform that ingests electronic healthcare claims by the millions. The system quickly identifies medical abuse, fraudulent healthcare charges and errors regardless of complexity. The system lists suspect issues and presents the data in clear visual and data formats, helping organizations appropriately address charges presented for payment.
Advanced Healthcare AI
The WhiteHatAI Centaur is an advanced AI driven forensic tool examining every line of every claim quickly and accurately while learning from every interaction it has with skilled medical claims professionals.
The Centaur amplifies the impact of subject matter experts, cost-effectively solving skilled labor shortages and dramatically increasing the effectiveness of skilled healthcare professionals.
The Centaur lists suspect issues through an easy to use summary framework and interface to help confirm, deny, dispute or renegotiate healthcare claims charges.
The WhiteHatAI Centaur system continuously learns from human interaction. The Centaur’s ability to detect healthcare fraud, waste and abuse becomes stronger with every example of medical billing abuse it encounters.
The Centaur’s powerful AI engines work around the clock to audit millions of claims, independently adjusting to new data while preventing millions of dollars of potential fraud, waste and abuse.
The Centaur provides a tool to help shift from a rules-based fraud detection approach to a true AI solution that investigates every claim while increasing auditing output, volume and accuracy.
The Centaur provides targeted, deep subject matter expertise to assist with medical claims reimbursement, preventing millions of dollars of fraud, waste and abuse while uncovering potential criminal activity.
Self-Insured payers are under unique financial. The Centaur provides self-insured organizations with powerful fraud detection AI tools, producing a cost-effective alternative to traditional scaling methods