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Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networks
冯博 靖
2021-02-12
Conference Name2020 IEEE 6th International Conference on Computer and Communications (ICCC)
Conference Date11-14 December 2020
Conference PlaceChengdu, China
Abstract

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.

Keywordcorporate credit ratings convolutional neural networks machine learning
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/48463
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. Every Corporation Owns Its Image: Corporate Credit Ratings via Convolutional Neural Networks[C],2021.
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