AI RESEARCH
STRIKE: Additive Feature-Group-Aware Stacking Framework for Credit Default Prediction
arXiv CS.LG
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ArXi:2604.17622v1 Announce Type: new Credit risk default prediction remains a cornerstone of risk management in the financial industry. The task involves estimating the likelihood that a borrower will fail to meet debt obligations, an objective critical for lending decisions, portfolio optimization, and regulatory compliance. Traditional machine learning models such as logistic regression and tree-based ensembles are widely adopted for their interpretability and strong empirical performance.