Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks

Eduardo Alarcon Morales; Brian Mora Ramos; Jimmy Armas Aguirre; David Mauricio Sanchez

doi:10.1109/CONIITI48476.2019.8960694

Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks

Eduardo Alarcon Morales
, Brian Mora Ramos
, Jimmy Armas Aguirre
, David Mauricio Sanchez

Facultad de Ingeniería

Universidad Peruana de Ciencias Aplicadas

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

1 Cita (Scopus)

Resumen

In this paper, we propose a risk analysis model to obtain the probability of default of microfinance clients in Peru. Our model uses trends of predictive analysis through variants of neural network algorithms; and data processing methodologies such as the Knowledge Discovery in Databases (KDD). The analysis method is used through Bayesian networks which allows the customer data evaluation and is related to our model data. This model is composed of 5 phases: 1. The input elements for the analysis; 2. The process of evaluation and analysis; 3. The regulatory standards; 4. The technological architecture; 5. The output elements. This model allows knowing the probability of compliance of a client with 84% prediction accuracy. The model validation was carried out in a microfinance institution in Lima, Peru, using cross-validation, evaluating the sensitivity and specificity of the results.

Idioma original	Inglés
Título de la publicación alojada	2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings
Editores	Monica Andrea Rico Martinez
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781728147468
DOI	https://doi.org/10.1109/CONIITI48476.2019.8960694
Estado	Publicada - oct. 2019
Evento	2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - 5th International Conference on Innovation and Trends in Engineering, CONIITI 2019 - Bogota, Colombia Duración: 2 oct. 2019 → 4 oct. 2019

Serie de la publicación

Nombre	2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings

Conferencia

Conferencia	2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - 5th International Conference on Innovation and Trends in Engineering, CONIITI 2019
País/Territorio	Colombia
Ciudad	Bogota
Período	2/10/19 → 4/10/19

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 1: Fin de la pobreza
ODS 5: Igualdad de género
ODS 8: Trabajo decente y crecimiento económico

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10.1109/CONIITI48476.2019.8960694

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Morales, E. A., Ramos, B. M., Aguirre, J. A., & Sanchez, D. M. (2019). Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks. En M. A. R. Martinez (Ed.), 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings Artículo 8960694 (2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONIITI48476.2019.8960694

Morales, Eduardo Alarcon ; Ramos, Brian Mora ; Aguirre, Jimmy Armas et al. / Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks. 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings. editor / Monica Andrea Rico Martinez. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings).

@inproceedings{56d9699ff04c4ecf81ce485345430d17,

title = "Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks",

abstract = "In this paper, we propose a risk analysis model to obtain the probability of default of microfinance clients in Peru. Our model uses trends of predictive analysis through variants of neural network algorithms; and data processing methodologies such as the Knowledge Discovery in Databases (KDD). The analysis method is used through Bayesian networks which allows the customer data evaluation and is related to our model data. This model is composed of 5 phases: 1. The input elements for the analysis; 2. The process of evaluation and analysis; 3. The regulatory standards; 4. The technological architecture; 5. The output elements. This model allows knowing the probability of compliance of a client with 84\% prediction accuracy. The model validation was carried out in a microfinance institution in Lima, Peru, using cross-validation, evaluating the sensitivity and specificity of the results.",

keywords = "Analysis algorithms, Bayesian networks, Credit Scoring, Data analysis, Microfinance, Moroseness, risk",

author = "Morales, \{Eduardo Alarcon\} and Ramos, \{Brian Mora\} and Aguirre, \{Jimmy Armas\} and Sanchez, \{David Mauricio\}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - 5th International Conference on Innovation and Trends in Engineering, CONIITI 2019 ; Conference date: 02-10-2019 Through 04-10-2019",

year = "2019",

month = oct,

doi = "10.1109/CONIITI48476.2019.8960694",

language = "Ingl{\'e}s",

series = "2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Martinez, \{Monica Andrea Rico\}",

booktitle = "2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings",

}

Morales, EA, Ramos, BM, Aguirre, JA & Sanchez, DM 2019, Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks. En MAR Martinez (ed.), 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings., 8960694, 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - 5th International Conference on Innovation and Trends in Engineering, CONIITI 2019, Bogota, Colombia, 2/10/19. https://doi.org/10.1109/CONIITI48476.2019.8960694

Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks. / Morales, Eduardo Alarcon; Ramos, Brian Mora; Aguirre, Jimmy Armas et al.
2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings. ed. / Monica Andrea Rico Martinez. Institute of Electrical and Electronics Engineers Inc., 2019. 8960694 (2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks

AU - Morales, Eduardo Alarcon

AU - Ramos, Brian Mora

AU - Aguirre, Jimmy Armas

AU - Sanchez, David Mauricio

PY - 2019/10

Y1 - 2019/10

N2 - In this paper, we propose a risk analysis model to obtain the probability of default of microfinance clients in Peru. Our model uses trends of predictive analysis through variants of neural network algorithms; and data processing methodologies such as the Knowledge Discovery in Databases (KDD). The analysis method is used through Bayesian networks which allows the customer data evaluation and is related to our model data. This model is composed of 5 phases: 1. The input elements for the analysis; 2. The process of evaluation and analysis; 3. The regulatory standards; 4. The technological architecture; 5. The output elements. This model allows knowing the probability of compliance of a client with 84% prediction accuracy. The model validation was carried out in a microfinance institution in Lima, Peru, using cross-validation, evaluating the sensitivity and specificity of the results.

AB - In this paper, we propose a risk analysis model to obtain the probability of default of microfinance clients in Peru. Our model uses trends of predictive analysis through variants of neural network algorithms; and data processing methodologies such as the Knowledge Discovery in Databases (KDD). The analysis method is used through Bayesian networks which allows the customer data evaluation and is related to our model data. This model is composed of 5 phases: 1. The input elements for the analysis; 2. The process of evaluation and analysis; 3. The regulatory standards; 4. The technological architecture; 5. The output elements. This model allows knowing the probability of compliance of a client with 84% prediction accuracy. The model validation was carried out in a microfinance institution in Lima, Peru, using cross-validation, evaluating the sensitivity and specificity of the results.

KW - Analysis algorithms

KW - Bayesian networks

KW - Credit Scoring

KW - Data analysis

KW - Microfinance

KW - Moroseness

KW - risk

UR - https://www.scopus.com/pages/publications/85079071172

U2 - 10.1109/CONIITI48476.2019.8960694

DO - 10.1109/CONIITI48476.2019.8960694

M3 - Contribución a la conferencia

AN - SCOPUS:85079071172

T3 - 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings

BT - 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings

A2 - Martinez, Monica Andrea Rico

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - 5th International Conference on Innovation and Trends in Engineering, CONIITI 2019

Y2 - 2 October 2019 through 4 October 2019

ER -

Morales EA, Ramos BM, Aguirre JA, Sanchez DM. Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks. En Martinez MAR, editor, 2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8960694. (2019 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2019 - Conference Proceedings). doi: 10.1109/CONIITI48476.2019.8960694

Credit Risk Analysis Model in Microfinance Institutions in Peru Through the use of Bayesian Networks

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