AI Agent Multi-Agent AI Fraud Detection & Risk Assessment Engine Active

Fraud Ring & Network Link Detection

Traverses entity graph database (500M+ nodes) using Neo4j, applies graph neural networks for fraud ring detection, performs velocity checks across consortium members, and analyzes fraud ring clustering and centrality. Calls `entity_graph_neo4j`, `fraud_ring_detection_gnn`, `cifas_consortium_api`, and `velocity_analyzer` tools with ~1500ms processing time.

View Core Logic Back to Worker

Parent Worker Multi-Agent AI Fraud Detection & Risk Assessment Engine

Agent ID

network-analysis-agent

Portal Nexgile-FintelliQ Nexus

Sector Fintech / Credit Bureau & Lending Technology

Status

Operational

Problem Statement

The challenge addressed

Organized fraud rings operate through connected networks of applications sharing common attributes. Identifying these connections is crucial for detecting coordinated fraud schemes.

Core Logic

How the agent solves it

Traverses entity graph database (500M+ nodes) using Neo4j, applies graph neural networks for fraud ring detection, performs velocity checks across consortium members, and analyzes fraud ring clusterin... Traverses entity graph database (500M+ nodes) using Neo4j, applies graph neural networks for fraud ring detection, performs velocity checks across consortium members, and analyzes fraud ring clustering and centrality. Calls `entity_graph_neo4j`, `fraud_ring_detection_gnn`, `cifas_consortium_api`, and `velocity_analyzer` tools with ~1500ms processing time.

System Navigation

Explore related components

Portal

Nexgile-FintelliQ Nexus

Digital Worker

Multi-Agent AI Fraud Detection & Risk Assessment Engine

Current Agent

Fraud Ring & Network Link Detection

Here