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Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks
Bo-Jing Feng; Xi Cheng; Hao-Nan Xu; Wen-Fang Xue
Source PublicationMachine Intelligence Research
ISSN2731-538X
2024
Volume21Issue:2Pages:257-271
AbstractIn order to help investors understand the credit status of target corporations and reduce investment risks, the corporate credit rating model has become an important evaluation tool in the financial market. These models are based on statistical learning, machine learning and deep learning especially graph neural networks (GNNs). However, we found that only few models take the hierarchy, heterogeneity or unlabeled data into account in the actual corporate credit rating process. Therefore, we propose a novel framework named hierarchical heterogeneous graph neural networks (HHGNN), which can fully model the hierarchy of corporate features and the heterogeneity of relationships between corporations. In addition, we design an adversarial learning block to make full use of the rich unlabeled samples in the financial data. Extensive experiments conducted on the public-listed corporate rating dataset prove that HHGNN achieves SOTA compared to the baseline methods.
KeywordCorporate credit rating, hierarchical relation, heterogeneous graph neural networks, adversarial learning
DOI10.1007/s11633-023-1425-9
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/56037
Collection学术期刊_Machine Intelligence Research
智能感知与计算研究中心
AffiliationCenter for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Bo-Jing Feng,Xi Cheng,Hao-Nan Xu,et al. Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks[J]. Machine Intelligence Research,2024,21(2):257-271.
APA Bo-Jing Feng,Xi Cheng,Hao-Nan Xu,&Wen-Fang Xue.(2024).Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks.Machine Intelligence Research,21(2),257-271.
MLA Bo-Jing Feng,et al."Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks".Machine Intelligence Research 21.2(2024):257-271.
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