Webinar on Fraud Detection with GNNs

Graph neural networks (GNN) are increasingly being used to identify suspicious behavior. GNNs can combine graph structures, such as email accounts, addresses, phone numbers, and purchasing behavior to find meaningful patterns and enhance fraud detection.

Join the webinar by Nikita Iserson, Senior ML/AI Architect at TigerGraph, to learn how graphs are used to uncover fraud on Thursday, Oct 27th, 6pm CET.

Agenda:

• Introduction to TigerGraph
• Fraud Detection Challenges
• Graph Model, Data Exploration, and Investigation
• Visual Rules, Red Flags, and Feature Generation
• TigerGraph Machine Learning Workbench
• XGBoost with Graph Features
• Graph Neural Network and Explainability