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