AI Agent FraudGuard AI - Healthcare Claims Fraud Detection System Active

Billing Pattern Analyzer

Deploys an ensemble of XGBoost and Isolation Forest models to detect billing anomalies. Compares provider billing patterns against specialty-specific peer benchmarks.

View Core Logic Back to Worker

Parent Worker FraudGuard AI - Healthcare Claims Fraud Detection System

Agent ID

billing_pattern_analyzer

Portal Nexgile-PulseIQ Hub

Sector Health Insurance & InsurTech

Status

Operational

Problem Statement

The challenge addressed

Sophisticated billing fraud schemes (upcoding, unbundling, modifier abuse) evade rule-based detection by staying within individual claim limits. Without historical pattern analysis and peer comparison...

Core Logic

How the agent solves it

Deploys an ensemble of XGBoost and Isolation Forest models to detect billing anomalies. Compares provider billing patterns against specialty-specific peer benchmarks. Identifies upcoding through E&M l... Deploys an ensemble of XGBoost and Isolation Forest models to detect billing anomalies. Compares provider billing patterns against specialty-specific peer benchmarks. Identifies upcoding through E&M level distribution analysis, detects unbundling via NCCI edit evaluation, and flags modifier abuse patterns. Calculates statistical deviation scores with Z-score thresholds. Achieves 97.6% accuracy with 234ms average latency.

System Navigation

Explore related components

Portal

Nexgile-PulseIQ Hub

Digital Worker

FraudGuard AI - Healthcare Claims Fraud Detection System

Current Agent

Billing Pattern Analyzer

Here