Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networks | |
冯博 靖 | |
2021-02-12 | |
会议名称 | 2020 IEEE 6th International Conference on Computer and Communications (ICCC) |
会议日期 | 11-14 December 2020 |
会议地点 | Chengdu, China |
摘要 | Credit rating is an analysis of the credit risks associated with a corporation, which reflect the level of the riskiness and reliability in investing. There have emerged many studies that implement machine learning techniques to deal with corporate credit rating. However, the ability of these models is limited by enormous amounts of data from financial statement reports. In this work, we analyze the performance of traditional machine learning models in predicting corporate credit rating. For utilizing the powerful convolutional neural networks and enormous financial data, we propose a novel end-to-end method, Corporate Credit Ratings via Convolutional Neural Networks, CCR-CNN for brevity. In the proposed model, each corporation is transformed into an image. Based on this image, CNN can capture complex feature interactions of data, which are difficult to be revealed by previous machine learning models. Extensive experiments conducted on the Chinese public-listed corporate rating dataset which we build, prove that CCR-CNN outperforms the state-of-the-art methods consistently. |
关键词 | corporate credit ratings convolutional neural networks machine learning |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48463 |
专题 | 智能感知与计算研究中心 |
作者单位 | 中科院自动化研究所 |
推荐引用方式 GB/T 7714 | 冯博 靖. Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networks[C],2021. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Every_Corporation_Ow(471KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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