Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context

Maïpa Pakidame; Komivi Ogbone; Yao Messah Kounetsron

doi:doi:10.11648/j.ijber.20200904.20

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Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context

Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron

Published in International Journal of Business and Economics Research (Volume 9, Issue 4)

Received: 30 March 2020 Accepted: 22 June 2020 Published: 22 July 2020

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Abstract

The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.

Published in	International Journal of Business and Economics Research (Volume 9, Issue 4) This article belongs to the Special Issue Microfinance and Local Development
DOI	10.11648/j.ijber.20200904.20
Page(s)	234-240
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), 2024. Published by Science Publishing Group

Keywords

Microfinance, DFS, Difficulties, Model, Early Warning

References

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[5]	Ayayi G. A. 2012, “Credit assessment in the microfinance industry”, Economics of Transition, 20, 1, pp 37-72.
[6]	Ayele G. T. 2015, “Microﬁnance Institutions in Ethiopia, Kenya and Uganda: Loan Outreach to the Poor and the Quest for Financial Viability”, African Development Review, 27, 2, pp 117-129.
[7]	Demirgüc-Kunt A., Detragiache E., 2005, "Cross-country Empirical Studies of Systemic Bank Distress: A Survey", National Institute Economic Review, National Institute of Economic and Social Research, 192, pp. 68 (16).
[8]	Eichengreen B., Arteta C., 2000, "Banking Crises in Emerging Markets: Presumptions and Evidence", Institute of Business and Economic Research, Center for International and development Economics Research, University of California.
[9]	Evans O., Leone A., Gill M., Hilbers P., 2000, "Macro prudential Indicators of Financial System Soundness", IMF, Occasional Paper, N° 192.
[10]	Gonzalez-Hermosillo B., 1999, " Crises bancaires: se doter d’indicateur d’alerte avancée ", IMF Finance & Development FMI.
[11]	Hardy D., Pazarbasioglu C., 1998, “Leading Indicators of Banking Crises: Was Asia Different? International Monetary Fund, Monetary and Exchange Affairs department, WP/98/91.
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[18]	Taccola-lapierre S., 2007, " La crise du subprime", Region et Développement, 26, pp. 52-63.

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APA Style

Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron. (2020). Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. International Journal of Business and Economics Research, 9(4), 234-240. https://doi.org/10.11648/j.ijber.20200904.20

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ACS Style

Maïpa Pakidame; Komivi Ogbone; Yao Messah Kounetsron. Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. Int. J. Bus. Econ. Res. 2020, 9(4), 234-240. doi: 10.11648/j.ijber.20200904.20

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AMA Style

Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron. Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. Int J Bus Econ Res. 2020;9(4):234-240. doi: 10.11648/j.ijber.20200904.20

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@article{10.11648/j.ijber.20200904.20,
  author = {Maïpa Pakidame and Komivi Ogbone and Yao Messah Kounetsron},
  title = {Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context},
  journal = {International Journal of Business and Economics Research},
  volume = {9},
  number = {4},
  pages = {234-240},
  doi = {10.11648/j.ijber.20200904.20},
  url = {https://doi.org/10.11648/j.ijber.20200904.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20200904.20},
  abstract = {The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.},
 year = {2020}
}

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TY  - JOUR
T1  - Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context
AU  - Maïpa Pakidame
AU  - Komivi Ogbone
AU  - Yao Messah Kounetsron
Y1  - 2020/07/22
PY  - 2020
N1  - https://doi.org/10.11648/j.ijber.20200904.20
DO  - 10.11648/j.ijber.20200904.20
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 234
EP  - 240
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20200904.20
AB  - The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.
VL  - 9
IS  - 4
ER  -

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Author Information

Maïpa Pakidame
Komivi Ogbone

University Institute of Technology of Management, Université de Lomé, Lomé, Togo
Yao Messah Kounetsron

University Institute of Technology of Management, Université de Lomé, Lomé, Togo

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Plain Text BibTeX RIS

APA Style

Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron. (2020). Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. International Journal of Business and Economics Research, 9(4), 234-240. https://doi.org/10.11648/j.ijber.20200904.20

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ACS Style

Maïpa Pakidame; Komivi Ogbone; Yao Messah Kounetsron. Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. Int. J. Bus. Econ. Res. 2020, 9(4), 234-240. doi: 10.11648/j.ijber.20200904.20

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AMA Style

Maïpa Pakidame, Komivi Ogbone, Yao Messah Kounetsron. Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context. Int J Bus Econ Res. 2020;9(4):234-240. doi: 10.11648/j.ijber.20200904.20

Copy | Download

@article{10.11648/j.ijber.20200904.20,
  author = {Maïpa Pakidame and Komivi Ogbone and Yao Messah Kounetsron},
  title = {Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context},
  journal = {International Journal of Business and Economics Research},
  volume = {9},
  number = {4},
  pages = {234-240},
  doi = {10.11648/j.ijber.20200904.20},
  url = {https://doi.org/10.11648/j.ijber.20200904.20},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20200904.20},
  abstract = {The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Anticipating the Difficulties of Microfinance Institutions: An Early Warning Model Applied to the Togolese Context
AU  - Maïpa Pakidame
AU  - Komivi Ogbone
AU  - Yao Messah Kounetsron
Y1  - 2020/07/22
PY  - 2020
N1  - https://doi.org/10.11648/j.ijber.20200904.20
DO  - 10.11648/j.ijber.20200904.20
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 234
EP  - 240
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20200904.20
AB  - The Decentralized financial system (DFS) is a sector in growth in developing countries. It offers financial services to actors rejected by formal banks because of their risk. therefore, a strict monitoring of this sector is needed to anticipate and avoid the bankruptcies of DFSs. In this context, an early warning model is a feasible solution. The aim of this paper is to develop a model of alert capable of predicting the difficulties of microfinance institutions. Data processed from 49 DFSs over 5 years led to a model explaining up to 80% of the likelihood of bankruptcy. Statistically positive results show that any increase in the portfolio at risk, the provisions on outstanding loans and the provisions on total assets leads to an increase in the probability of difficulty for the DFSs, thus increasing its insolvency risk while any increase in the equity risk coverage ratio, the operating income on owner’s equity, the loan coverage by deposits ratio, the profit margin and the outstanding deposits on total assets leads to a decrease in the probability of default for the DFSs.
VL  - 9
IS  - 4
ER  -

Copy | Download