Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks

doi:10.1007/s11633-023-1425-9

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	Corporate Credit Ratings Based on Hierarchical Heterogeneous Graph Neural Networks
	Bo-Jing Feng; Xi Cheng; Hao-Nan Xu; Wen-Fang Xue
发表期刊	Machine Intelligence Research
ISSN	2731-538X
	2024
卷号	21 期号:2 页码:257-271
摘要	In 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.
关键词	Corporate credit rating, hierarchical relation, heterogeneous graph neural networks, adversarial learning
DOI	10.1007/s11633-023-1425-9
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/56037
专题	学术期刊_Machine Intelligence Research 模式识别实验室
作者单位	Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
第一作者单位	模式识别国家重点实验室
推荐引用方式 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.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
MIR-2022-11-330.pdf（2621KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载