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Title: A Multi-Class Model to Predict the Result of the Legal Insolvency Proceedings
Authors: Pastor-Vega, Daniel
Fernández-Miguélez, Sergio M.
Diéguez-Soto, Julio
Fernández-Gámez, Manuel A
Keywords: Insolvency proceedings;Insolvency prediction;Business bankruptcy;Financial distress;Multi-class classifiers;Naive Bayes
Issue Date: Nov-2019
Publisher: NISCAIR-CSIR, India
Abstract: A small number of studies have been carried out to build models with which to predict the results of the insolvency proceedings. In addition, there are no models that have demonstrated a high predictive capacity for all situations in which such legal processes can end. The proposal of this study is the construction of a multi-class model that predicts with high precision the possible future situations of companies that are in legal insolvency proceedings. The results of this study reveal that using the Naive Bayes classifier the model achieves an accuracy of more than 91% and that the best predictors are variables related to the profitability, efficiency and volume of resources generated by the companies.
Page(s): 742-745
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.78(11) [November 2019]

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