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Bankruptcy Prediction Model Based on Business Risk Reports : Use of Natural Language Processing Techniques

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/81088

Title: Bankruptcy Prediction Model Based on Business Risk Reports : Use of Natural Language Processing Techniques
Authors: Rasolomanana, Onjaniaina Mianin'Harizo Browse this author
Keywords: Bankruptcy prediction
Business risk
Natural language processing
NLP
Sentiment analysis
Neural Networks
Issue Date: Apr-2021
Publisher: Faculty of Economics and Business, Hokkaido University
Journal Title: Discussion Paper, Series A
Volume: 358
Start Page: 1
End Page: 14
Abstract: The purpose of this study is to assess how useful risk information is in bankruptcy prediction, by performing a sentiment analysis of the texts. The proposed method involves the use of Natural Language Processing (NLP) and machine learning techniques. The results show that neural networks performed better than other classifiers, with a classification accuracy of 96.15% for this particular text classification problem. This work demonstrates that business risks reports carry information that helps predict the likelihood of bankruptcy.
Type: bulletin (article)
URI: http://hdl.handle.net/2115/81088
Appears in Collections:Discussion paper > Series A

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