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Explainable enterprise credit rating using deep feature crossing
Weiyu Guo1; Zhijiang Yang2; Shu Wu3; Fu Chen1; Xiuli Wang1; Fu Chen1
Source PublicationExpert Systems With Applications
2023-06-15
Volume220Issue:cPages:1-12
Abstract

Deep Neural Networks (DNNs) have powerful learning abilities on high-rank and non-linear features, and thus have been applied to various fields, exhibiting higher discrimination performance than conventional methods. However, their applications in enterprise credit rating tasks are rare, as most DNNs employ the “end-to-end” learning paradigm, producing high-rank representations of objects or predictive results without any explanations. This “black box” approach makes it difficult for users in the financial industry to understand how these predictive results are generated, or what correlations exist with the raw inputs, leading to a lack of trust to the predictions. To address this issue, this paper proposes a novel network to explicitly model the enterprise credit rating problem using DNNs and attention mechanisms, allowing for explainable enterprise credit ratings. Experiments conducted on real-world enterprise datasets show that the proposed approach achieves higher performance than conventional methods, while also providing insights into individual rating results and the reliability of model training. The code is provided on .

Language英语
Sub direction classification机器学习
planning direction of the national heavy laboratory智能计算与学习
Paper associated data
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57447
Collection模式识别实验室
Affiliation1.中央财经大学
2.National University of Singapore
3.中国科学院自动化研究所
Recommended Citation
GB/T 7714
Weiyu Guo,Zhijiang Yang,Shu Wu,et al. Explainable enterprise credit rating using deep feature crossing[J]. Expert Systems With Applications,2023,220(c):1-12.
APA Weiyu Guo,Zhijiang Yang,Shu Wu,Fu Chen,Xiuli Wang,&Fu Chen.(2023).Explainable enterprise credit rating using deep feature crossing.Expert Systems With Applications,220(c),1-12.
MLA Weiyu Guo,et al."Explainable enterprise credit rating using deep feature crossing".Expert Systems With Applications 220.c(2023):1-12.
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