CASIA OpenIR  > 智能感知与计算
Adversarial Semi-supervised Learning for Corporate Credit Ratings
冯博 靖
Source PublicationJournal of Software
2021
Volume16Issue:6Pages:259-266
Abstract

Corporate credit rating is an analysis of credit risks withina corporation, which plays a vital role during the management of financial risk. Traditionally, the rating assessment process based on the historical profile of corporation is usually expensive and complicated, which often takes months. Therefore, most of the corporations, duetothelack in money and time, can’t get their own credit level. However, we believe that although these corporations haven’t their credit rating levels (unlabeled data), this big data contains useful knowledgeto improve credit system. In this work, its major challenge lies in how to effectively learn the knowledge from unlabeled data and help improve the performance of the credit rating system. Specifically, we consider the problem of adversarial semi-supervised learning (ASSL) for corporate credit rating which has been rarely researched before. A novel framework adversarial semi-supervised learning for corporate credit rating (ASSL4CCR) which includes two phases is proposed to address these problems. In the first phase, we train a normal rating system via a machine-learning algorithm to give unlabeled data pseudo rating level. Then in the second phase, adversarial semi-supervised learning is applied uniting labeled data and pseudo-labeleddatato build the final model. To demonstrate the effectiveness of the proposed ASSL4CCR, we conduct extensive experiments on the Chinese public-listed corporate rating dataset, which proves that ASSL4CCR outperforms the state-of-the-art methods consistently.

KeywordAdversarial learning corporate credit ratings financial risk semi-supervised learning
Indexed By其他
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/48467
Collection智能感知与计算
Affiliation中科院自动化研究所
Recommended Citation
GB/T 7714
冯博 靖. Adversarial Semi-supervised Learning for Corporate Credit Ratings[J]. Journal of Software,2021,16(6):259-266.
APA 冯博 靖.(2021).Adversarial Semi-supervised Learning for Corporate Credit Ratings.Journal of Software,16(6),259-266.
MLA 冯博 靖."Adversarial Semi-supervised Learning for Corporate Credit Ratings".Journal of Software 16.6(2021):259-266.
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