Valentis

AI-Powered Revenue & Fraud Intelligence for Healthcare!

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Valentis

AI-Powered Revenue & Fraud Intelligence for Healthcare

Inspiration

Hospitals lose billions annually due to patient payment delinquency, insurance underpayments, refund abuse, and operational blind spots within revenue cycle systems. Most billing platforms are reactive — identifying issues only after revenue has already been lost.

With shrinking margins and rising financial pressure, delayed insight is no longer acceptable. Revenue cycle teams need visibility before accounts reach bad debt.

We built Valentis to shift healthcare finance from reactive reporting to predictive intelligence — empowering teams to detect risk early, prevent fraud, and protect financial stability before losses occur.

What It Does

Valentis is a predictive revenue intelligence platform that:

  • Forecasts patient payment delinquency using machine learning
  • Detects refund abuse and suspicious transaction patterns
  • Identifies anomalous financial activity across departments
  • Projects revenue at risk over the next 30 days
  • Recommends optimized payment plan strategies based on risk scoring
  • Monitors internal system access logs for compliance and insider risk

Instead of static billing reports, teams receive actionable dashboards, fraud alerts, and forward-looking revenue risk projections.

How We Built It

Valentis is a full-stack web application designed for scalability and security.

Frontend

  • React 18
  • Vite
  • Recharts
  • React Router

Backend

  • FastAPI
  • Pandas
  • NumPy
  • Scikit-learn

Machine Learning

  • Logistic Regression for delinquency prediction
  • Isolation Forest for fraud detection
  • Z-score anomaly detection for unusual activity

Data Architecture

  • Secure ZIP upload of de-identified CSV datasets
  • SQLite (demo) with in-memory processing
  • Modular backend structure (routers, services, models, schemas)

Security & Privacy

Valentis is built with HIPAA-aligned principles:

  • De-identified account IDs only (no PHI stored)
  • Role-based access control
  • Two-factor authentication
  • Comprehensive audit logging
  • Data minimization
  • Encrypted communication

Security is foundational to the platform’s design.

Challenges We Faced

  • Designing realistic fraud detection models within hackathon constraints
  • Creating synthetic datasets that reflect real hospital billing complexity
  • Balancing predictive accuracy with real-time dashboard performance
  • Implementing security-first architecture under time pressure

Accomplishments

  • Built an end-to-end predictive revenue intelligence system
  • Integrated multiple ML models into a unified dashboard
  • Delivered enterprise-grade UX tailored to hospital finance teams
  • Implemented security controls beyond typical hackathon scope

What We Learned

  • Healthcare revenue cycles are deeply complex and highly data-driven
  • Fraud detection requires combining statistical modeling with contextual rules
  • Security must be embedded from the beginning
  • Clear UX design is critical for operational enterprise tools

What’s Next for Valentis

  • Real-time API integrations with hospital billing systems
  • Secure cloud deployment with monitoring and role-based access
  • SSO integration (SAML / OAuth)
  • Payer-level underpayment analysis
  • Continuous model improvement with retraining pipelines
  • Configurable risk thresholds and alerts
  • Exportable audit and compliance reports
  • Pilot partnerships for real-world validation

Valentis aims to be a practical, secure intelligence layer that helps hospitals proactively manage risk and protect revenue.

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