DeRisk: An Effective Deep Learning Framework for Credit Risk Prediction over Real-World Financial Data

Despite the tremendous advances achieved over the past years by deep learning techniques, the latest risk prediction models for industrial applications still rely on highly handtuned stage-wised statistical learning tools, such as gradient boosting and random forest methods. Different from images or...

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Veröffentlicht in:	arXiv.org 2023-08
Hauptverfasser:	Liang, Yancheng, Zhang, Jiajie, Li, Hui, Liu, Xiaochen, Hu, Yi, Wu, Yong, Zhang, Jinyao, Liu, Yongyan, Wu, Yi
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Artificial neural networks Deep learning Industrial applications Machine learning Prediction models Risk
Online-Zugang:	Volltext
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