Explainable Graph Neural Networks for Interbank Contagion Surveillance: A Regulatory-Aligned Framework for the U.S. Banking Sector

The ST-GAT framework provides an explainable Graph Neural Network solution for early detection of bank distress and interbank contagion surveillance in the U.S. banking sector. It models over 8,000 FDIC institutions using dynamic graphs, achieving high performance (AUPRC 0.939) and identifying key predictive factors like ROA and NPL Ratio.