Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers

Alevtina Shatalova; Konstantin Lebedev; Igor Shevchenko; Boureima Bamadio

doi:doi:10.11648/j.engmath.20200401.12

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Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers

Alevtina Shatalova, Konstantin Lebedev, Igor Shevchenko, Boureima Bamadio

Published in Engineering Mathematics (Volume 4, Issue 1)

Received: 13 August 2019 Accepted: 6 September 2019 Published: 28 May 2020

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Abstract

The article describes the Altman Five-factor Model to assess the creditworthiness of the enterprise with the apparatus of the theory of fuzzy sets. There were two improvements. The early method used the square integral approximation for the accurately calculating of the quantitative assessment of creditworthiness and the apparatus of fuzzy sets for ordering the sets according to the degree of confidence of the probability obtained. The new method described in this article is expanded by presenting the input data as triangular fuzzy numbers. This article describes the simulation of the credit assessment procedure and the possibility of functioning of the model as well. This approach helps to adequately assess the creditworthiness of the enterprise, also to make it possible to predict the change in the result of the model due to possible errors in the input data. The results were tested at the Krasnodar cryptic plant.

Published in	Engineering Mathematics (Volume 4, Issue 1)
DOI	10.11648/j.engmath.20200401.12
Page(s)	10-13
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Assessment of the Creditworthiness, Altman Model, Fuzzy Sets, Membership Function, Simulation, Decision-making Under Uncertainty, Errors in the Financial Statements

References

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Alevtina Shatalova, Konstantin Lebedev, Igor Shevchenko, Boureima Bamadio. (2020). Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers. Engineering Mathematics, 4(1), 10-13. https://doi.org/10.11648/j.engmath.20200401.12

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ACS Style

Alevtina Shatalova; Konstantin Lebedev; Igor Shevchenko; Boureima Bamadio. Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers. Eng. Math. 2020, 4(1), 10-13. doi: 10.11648/j.engmath.20200401.12

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AMA Style

Alevtina Shatalova, Konstantin Lebedev, Igor Shevchenko, Boureima Bamadio. Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers. Eng Math. 2020;4(1):10-13. doi: 10.11648/j.engmath.20200401.12

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@article{10.11648/j.engmath.20200401.12,
  author = {Alevtina Shatalova and Konstantin Lebedev and Igor Shevchenko and Boureima Bamadio},
  title = {Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers},
  journal = {Engineering Mathematics},
  volume = {4},
  number = {1},
  pages = {10-13},
  doi = {10.11648/j.engmath.20200401.12},
  url = {https://doi.org/10.11648/j.engmath.20200401.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.engmath.20200401.12},
  abstract = {The article describes the Altman Five-factor Model to assess the creditworthiness of the enterprise with the apparatus of the theory of fuzzy sets. There were two improvements. The early method used the square integral approximation for the accurately calculating of the quantitative assessment of creditworthiness and the apparatus of fuzzy sets for ordering the sets according to the degree of confidence of the probability obtained. The new method described in this article is expanded by presenting the input data as triangular fuzzy numbers. This article describes the simulation of the credit assessment procedure and the possibility of functioning of the model as well. This approach helps to adequately assess the creditworthiness of the enterprise, also to make it possible to predict the change in the result of the model due to possible errors in the input data. The results were tested at the Krasnodar cryptic plant.},
 year = {2020}
}

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TY  - JOUR
T1  - Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers
AU  - Alevtina Shatalova
AU  - Konstantin Lebedev
AU  - Igor Shevchenko
AU  - Boureima Bamadio
Y1  - 2020/05/28
PY  - 2020
N1  - https://doi.org/10.11648/j.engmath.20200401.12
DO  - 10.11648/j.engmath.20200401.12
T2  - Engineering Mathematics
JF  - Engineering Mathematics
JO  - Engineering Mathematics
SP  - 10
EP  - 13
PB  - Science Publishing Group
SN  - 2640-088X
UR  - https://doi.org/10.11648/j.engmath.20200401.12
AB  - The article describes the Altman Five-factor Model to assess the creditworthiness of the enterprise with the apparatus of the theory of fuzzy sets. There were two improvements. The early method used the square integral approximation for the accurately calculating of the quantitative assessment of creditworthiness and the apparatus of fuzzy sets for ordering the sets according to the degree of confidence of the probability obtained. The new method described in this article is expanded by presenting the input data as triangular fuzzy numbers. This article describes the simulation of the credit assessment procedure and the possibility of functioning of the model as well. This approach helps to adequately assess the creditworthiness of the enterprise, also to make it possible to predict the change in the result of the model due to possible errors in the input data. The results were tested at the Krasnodar cryptic plant.
VL  - 4
IS  - 1
ER  -

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Author Information

Alevtina Shatalova

Department of Applied Mathematics, Kuban State University, Krasnodar, Russia
Konstantin Lebedev

Department of Applied Mathematics, Kuban State University, Krasnodar, Russia
Igor Shevchenko

Faculty of Economics, Кuban State University, Krasnodar, Russia
Boureima Bamadio

Faculty of Economics and Management, University of Social Sciences and Management of Bamako, Mali, Bamako

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Plain Text BibTeX RIS

APA Style

Alevtina Shatalova, Konstantin Lebedev, Igor Shevchenko, Boureima Bamadio. (2020). Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers. Engineering Mathematics, 4(1), 10-13. https://doi.org/10.11648/j.engmath.20200401.12

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ACS Style

Alevtina Shatalova; Konstantin Lebedev; Igor Shevchenko; Boureima Bamadio. Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers. Eng. Math. 2020, 4(1), 10-13. doi: 10.11648/j.engmath.20200401.12

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AMA Style

Alevtina Shatalova, Konstantin Lebedev, Igor Shevchenko, Boureima Bamadio. Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers. Eng Math. 2020;4(1):10-13. doi: 10.11648/j.engmath.20200401.12

Copy | Download

@article{10.11648/j.engmath.20200401.12,
  author = {Alevtina Shatalova and Konstantin Lebedev and Igor Shevchenko and Boureima Bamadio},
  title = {Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers},
  journal = {Engineering Mathematics},
  volume = {4},
  number = {1},
  pages = {10-13},
  doi = {10.11648/j.engmath.20200401.12},
  url = {https://doi.org/10.11648/j.engmath.20200401.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.engmath.20200401.12},
  abstract = {The article describes the Altman Five-factor Model to assess the creditworthiness of the enterprise with the apparatus of the theory of fuzzy sets. There were two improvements. The early method used the square integral approximation for the accurately calculating of the quantitative assessment of creditworthiness and the apparatus of fuzzy sets for ordering the sets according to the degree of confidence of the probability obtained. The new method described in this article is expanded by presenting the input data as triangular fuzzy numbers. This article describes the simulation of the credit assessment procedure and the possibility of functioning of the model as well. This approach helps to adequately assess the creditworthiness of the enterprise, also to make it possible to predict the change in the result of the model due to possible errors in the input data. The results were tested at the Krasnodar cryptic plant.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Improving the Altman Method for Assess the Creditworthiness of Enterprises with Economic Indicators in the Form of Fuzzy Numbers
AU  - Alevtina Shatalova
AU  - Konstantin Lebedev
AU  - Igor Shevchenko
AU  - Boureima Bamadio
Y1  - 2020/05/28
PY  - 2020
N1  - https://doi.org/10.11648/j.engmath.20200401.12
DO  - 10.11648/j.engmath.20200401.12
T2  - Engineering Mathematics
JF  - Engineering Mathematics
JO  - Engineering Mathematics
SP  - 10
EP  - 13
PB  - Science Publishing Group
SN  - 2640-088X
UR  - https://doi.org/10.11648/j.engmath.20200401.12
AB  - The article describes the Altman Five-factor Model to assess the creditworthiness of the enterprise with the apparatus of the theory of fuzzy sets. There were two improvements. The early method used the square integral approximation for the accurately calculating of the quantitative assessment of creditworthiness and the apparatus of fuzzy sets for ordering the sets according to the degree of confidence of the probability obtained. The new method described in this article is expanded by presenting the input data as triangular fuzzy numbers. This article describes the simulation of the credit assessment procedure and the possibility of functioning of the model as well. This approach helps to adequately assess the creditworthiness of the enterprise, also to make it possible to predict the change in the result of the model due to possible errors in the input data. The results were tested at the Krasnodar cryptic plant.
VL  - 4
IS  - 1
ER  -

Copy | Download