Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models

In three linesComparative study of tabular foundation models (TFMs) vs classical models on credit default prediction. On Home Credit and Lending Club datasets, context construction strategy (balanced vs uniform sampling) explains more AUC-ROC variance than model choice: +3-4 AUC points. With 5K-10K balanced examples, TFMs match classical GBDTs while improving default-class recall.

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