CSA-Net: a cost-sensitive adaptive hybrid framework for imbalanced financial distress prediction
Researchers have developed CSA-Net, a cost-sensitive adaptive hybrid framework designed to improve the accuracy of financial distress predictions for firms. The model combines tree-based boosting with neural residuals to better handle imbalanced datasets where distressed firms are rare.
Why it matters
Improving bankruptcy prediction models helps financial institutions and regulators mitigate economic risks and prevent systemic failures.
Scientific Reports ( 2026 ) Cite this article
We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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