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Bankruptcy prediction using machine learning models: empirical results in the Colombian manufacturing industry (2018-2022)
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Autores
Orientador(es)
Resumo(s)
The purpose of this study is to examine financial indicators that reveal the situation of corporate
failure in manufacturing companies in Colombia. The use of these indicators is based on previous
studies that have used predictive models of corporate fragility: multiple discriminant analysis,
logistic regression, and machine learning. This work uses logistic regression and random forests
models. This work is based on financial indicators made of the data reported between 2018 and
2022 in the database Sistema de Información y Riesgos Empresariales (SIREM) of the
Superintendence of Companies.
Descrição
Palavras-chave
Corporate insolvency Business failure Insolvency prediction Bankruptcy Financial analysis Financial ratios Random forest