Feng Zhao
Feng is a senior data scientist at Adyen. He is passionate about solving real business problems using innovative AI/machine learning approaches. He received his Ph.D. from the National University of Singapore.
Sessions
Fraud is a major problem for financial services companies. As fraudsters change tactics, our detection methods need to get smarter. Graph neural networks (GNNs) are a promising model to improve detection performance. Unlike traditional machine learning models or rule-based engines, GNNs can effectively learn from subtle relationships by aggregating neighborhood information in the financial transaction networks. However, it remains a challenge to adopt this new approach in production.
The goal of this talk is to share best practices for building a production ready GNN solution and hopefully spark your interest to apply GNNs to your own use cases.