Analysis of a Bankruptcy Prediction Model for Companies in Chile

Benito Umaña-Hermosilla; Hanns de la Fuente-Mella; Claudio Elórtegui-Gómez; Jorge Ferrada-Rodríguez; Mauricio Arce-Rojas

doi:10.1007/978-3-030-80624-8_11

Analysis of a Bankruptcy Prediction Model for Companies in Chile

Benito Umaña-Hermosilla, Hanns de la Fuente-Mella, Claudio Elórtegui-Gómez, Jorge Ferrada-Rodríguez, Mauricio Arce-Rojas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The objective of this research is to examine bankruptcy prediction models and their application in companies in Chile. For this, bankruptcy regulations in Chile and internationally, specifically the United States and Colombia, are analyzed. In turn, the procedures that companies can use today are examined. In addition, the existing prediction models are compared. The model chosen for the development of the research is the Altman Z-score, with which it is sought to confirm its validity, applying it to Chilean companies. For this research, companies were classified into two groups: healthy companies and companies with financial problems. According to the results, the Altman Z-score model on companies, five companies could be found which may need to take advantage of bankruptcy regulations.

Original language	English
Title of host publication	Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021
Editors	Tareq Z. Ahram, Waldemar Karwowski, Jay Kalra
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	83-90
Number of pages	8
ISBN (Print)	9783030806231
DOIs	https://doi.org/10.1007/978-3-030-80624-8_11
State	Published - 2021
Event	AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 - Virtual, Online Duration: 25 Jul 2021 → 29 Jul 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	271
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021
City	Virtual, Online
Period	25/07/21 → 29/07/21

Keywords

Bankruptcy
Econometric modeling
Insolvency
Liquidation and reorganization

Access to Document

10.1007/978-3-030-80624-8_11

Cite this

Umaña-Hermosilla, B., de la Fuente-Mella, H., Elórtegui-Gómez, C., Ferrada-Rodríguez, J., & Arce-Rojas, M. (2021). Analysis of a Bankruptcy Prediction Model for Companies in Chile. In T. Z. Ahram, W. Karwowski, & J. Kalra (Eds.), Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 (pp. 83-90). (Lecture Notes in Networks and Systems; Vol. 271). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-80624-8_11

Umaña-Hermosilla, Benito ; de la Fuente-Mella, Hanns ; Elórtegui-Gómez, Claudio et al. / Analysis of a Bankruptcy Prediction Model for Companies in Chile. Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. editor / Tareq Z. Ahram ; Waldemar Karwowski ; Jay Kalra. Springer Science and Business Media Deutschland GmbH, 2021. pp. 83-90 (Lecture Notes in Networks and Systems).

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title = "Analysis of a Bankruptcy Prediction Model for Companies in Chile",

abstract = "The objective of this research is to examine bankruptcy prediction models and their application in companies in Chile. For this, bankruptcy regulations in Chile and internationally, specifically the United States and Colombia, are analyzed. In turn, the procedures that companies can use today are examined. In addition, the existing prediction models are compared. The model chosen for the development of the research is the Altman Z-score, with which it is sought to confirm its validity, applying it to Chilean companies. For this research, companies were classified into two groups: healthy companies and companies with financial problems. According to the results, the Altman Z-score model on companies, five companies could be found which may need to take advantage of bankruptcy regulations.",

keywords = "Bankruptcy, Econometric modeling, Insolvency, Liquidation and reorganization",

author = "Benito Uma{\~n}a-Hermosilla and {de la Fuente-Mella}, Hanns and Claudio El{\'o}rtegui-G{\'o}mez and Jorge Ferrada-Rodr{\'i}guez and Mauricio Arce-Rojas",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.; AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 ; Conference date: 25-07-2021 Through 29-07-2021",

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doi = "10.1007/978-3-030-80624-8_11",

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Umaña-Hermosilla, B, de la Fuente-Mella, H, Elórtegui-Gómez, C, Ferrada-Rodríguez, J & Arce-Rojas, M 2021, Analysis of a Bankruptcy Prediction Model for Companies in Chile. in TZ Ahram, W Karwowski & J Kalra (eds), Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. Lecture Notes in Networks and Systems, vol. 271, Springer Science and Business Media Deutschland GmbH, pp. 83-90, AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021, Virtual, Online, 25/07/21. https://doi.org/10.1007/978-3-030-80624-8_11

Analysis of a Bankruptcy Prediction Model for Companies in Chile. / Umaña-Hermosilla, Benito; de la Fuente-Mella, Hanns; Elórtegui-Gómez, Claudio et al.
Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. ed. / Tareq Z. Ahram; Waldemar Karwowski; Jay Kalra. Springer Science and Business Media Deutschland GmbH, 2021. p. 83-90 (Lecture Notes in Networks and Systems; Vol. 271).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - de la Fuente-Mella, Hanns

AU - Elórtegui-Gómez, Claudio

AU - Ferrada-Rodríguez, Jorge

AU - Arce-Rojas, Mauricio

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AB - The objective of this research is to examine bankruptcy prediction models and their application in companies in Chile. For this, bankruptcy regulations in Chile and internationally, specifically the United States and Colombia, are analyzed. In turn, the procedures that companies can use today are examined. In addition, the existing prediction models are compared. The model chosen for the development of the research is the Altman Z-score, with which it is sought to confirm its validity, applying it to Chilean companies. For this research, companies were classified into two groups: healthy companies and companies with financial problems. According to the results, the Altman Z-score model on companies, five companies could be found which may need to take advantage of bankruptcy regulations.

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Umaña-Hermosilla B, de la Fuente-Mella H, Elórtegui-Gómez C, Ferrada-Rodríguez J, Arce-Rojas M. Analysis of a Bankruptcy Prediction Model for Companies in Chile. In Ahram TZ, Karwowski W, Kalra J, editors, Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021. Springer Science and Business Media Deutschland GmbH. 2021. p. 83-90. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-80624-8_11

Analysis of a Bankruptcy Prediction Model for Companies in Chile

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