This Guidance demonstrates an end-to-end, near real-time anti-fraud system based on deep learning graph neural networks. This blueprint architecture uses Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network (GNN) model to detect fraudulent transactions.
