Hybrid XGBoost model on CFPB complaints achieves AUC-ROC of 0.78 for predicting monetary relief, outperforming TF-IDF baseline of 0.69.
banking: integrating OCC, SR 11-7, CFPB, and FinCEN compliance requirements for model development, validation, and monitoring lifecycles
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From Complaint Narratives to Monetary Relief: A Hybrid Machine Learning Framework for CFPB Consumer Complaints
Hybrid XGBoost model on CFPB complaints achieves AUC-ROC of 0.78 for predicting monetary relief, outperforming TF-IDF baseline of 0.69.