ST-GAT applies spatial-temporal graph attention networks to reconstructed interbank graphs from FDIC Call Reports, achieving 0.939 AUPRC for bank distress prediction with explainable feature importance.
Bootstrap confidence intervals (1,000 resamples, median CI across seeds) are reported in the AUROC 95% CI column of Table 1 for models evaluated across 5 seeds
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Explainable Graph Neural Networks for Interbank Contagion Surveillance: A Regulatory-Aligned Framework for the U.S. Banking Sector
ST-GAT applies spatial-temporal graph attention networks to reconstructed interbank graphs from FDIC Call Reports, achieving 0.939 AUPRC for bank distress prediction with explainable feature importance.