Alivia Analytics

Founded by Kleber Gallardo in 2018

Detect and prevent healthcare fraud, waste, and abuse before claims are paid

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You can use Alivia Analytics to identify fraudulent healthcare claims before and after payment using AI-based behavioral modeling and analytics. It flags high-risk providers pre-payment, runs post-payment investigations to recover improper payments, standardizes claims data for analysis, and manages Special Investigation Unit (SIU) case workflows. The system targets the gray zone between errors, fraud, waste, and abuse that rules-based systems typically miss. It serves Medicaid, Medicare, commercial health plans, TPAs, and self-insured employers of all sizes.

What Alivia Analytics does

Score provider claims for fraud risk before payment approvalRun investigations on post-payment claims to identify recoverable overpaymentsManage SIU case workflows from lead generation to case closureIngest and standardize claims data from multiple sources into analytics-ready formatsConfigure pend-and-review triggers for high-risk claim categoriesGenerate reports on fraud, waste, and abuse patterns across provider networksMigrate and optimize legacy claims systems for payersFlags high-risk providers before payment using advanced scoring and configurable pend-and-review triggersUncovers hidden fraud leads and accelerates SIU investigations post-paymentTargets gray zone between errors, fraud, waste, and abuse missed by rules-based systemsStandardizes claims data into analytics-ready formats via DataChromeSupports case management workflows for SIU teams with Alivia Case ManagerIncludes clinical audits and data mining to recover overlooked improper paymentsAI acts as an optional assistant with human oversight and compliance controlsCovers both government and commercial payers including Medicaid, Medicare, TPAs, and self-insured employers

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