Isolating Graph Topology from Model Architecture in GNN-Based Fraud Detection: An Empirical Framework
Graph topology and model architecture are routinely co-designed in GNN-based fraud detection, making it impossible to attribute performance gains to either component. We address this by fixing the training loop, features, and evaluation protocol while independently varying the graph construction strategy and GNN archit...