FraudGraph™: Network-Based Syndicate & Ring Explorer
Traditional rules evaluate single claims in isolation. FraudGraph™ builds an interconnected multi-million entity knowledge graph to uncover invisible collusions between hospitals, doctors, labs, brokers, and patients.
Interactive Healthcare Network Visualizer
Click on any entity to view degree centrality, historical claim volumes, and active ring risk flags.
The 4 Hidden Fraud Archetypes We Detect
Uncovering systemic collusions that cause multi-crore losses across insurance books.
The High-Volume Broker-Surgeon Funnel
A specific insurance broker funnels dozens of healthy corporate employees to a single surgeon for elective procedures (e.g. arthroscopy, bariatric, high-end stent implants) with exaggerated diagnostic severity.
Ghost Diagnostic Lab Billing Nexus
A diagnostic facility bills for expensive specialized pathology and molecular gene panels across hundreds of patients who were never physically present in the lab.
Cross-Hospital Cloned Discharge Summaries
A coordinated ring re-submits identical medical histories, operative summaries, and nursing charts by only altering the patient name and date.
Simultaneous Multi-Policy Overlap
The same hospitalization event is billed in parallel to two different private insurers and a state government health scheme (PM-JAY) by splitting invoices.
Why Knowledge Graphs Are Impossible to Replicate with Basic LLMs
An LLM can only read the PDF in front of it. It has zero memory of the 200,000 claims submitted last quarter across other hospitals. FraudGraph™ maintains continuous entity resolution, forming an irreplaceable proprietary data moat.
Uncover Fraud Rings in Your Claims Portfolio
Run a pilot graph audit on your provider network to identify anomalous clusters and circular referral rings.