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AI-Powered Claims Intelligence
Detecting Fraud, Waste & Abuse
That Payers are Missing Today
ClaimQI deploys machine learning and large language models trained on claims patterns and FW&A signatures that go beyond today's traditional systems. Identify financial leakage that legacy systems simply can't see.
(Pronounced "Claim-Chee")
$300B+
Lost annually to healthcare fraud, waste & abuse in the U.S.
Source: NHCAA / CMS estimates
~10%
Of all healthcare spending is lost to FW&A, the majority paid before detection.
Source: CMS, FBI Healthcare Fraud Division
<1%
Of fraudulent claims detected by traditional rule-based payer systems
Source: OIG / industry research
Legacy systems alone leave dollars unrecovered
Today's Payers are Flying Blind
Medicare Plans and TPAs rely on legacy rules engines and retrospective audits. By the time fraud is detected, the money is already gone. In addition, only a fraction of improper payments
(otherwise known as waste & abuse) are being identified and/or properly explained
to support recovery efforts.
Rules engines lack sufficient scale and intelligence
THE PROBLEM
TPAs lack Intelligent infrastructure and information
Claims navigation lacks pin-point accuracy and detail
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