Data science model for the evaluation of customers of rural savings banks without credit history

Aldo David Caceres Gonzales; Fabio Leonel Paucar Villantoy; David Santos Mauricio Sanchez

doi:10.1109/IESTEC46403.2019.00067

Data science model for the evaluation of customers of rural savings banks without credit history

Aldo David Caceres Gonzales, Fabio Leonel Paucar Villantoy, David Santos Mauricio Sanchez

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

1 Cita (Scopus)

Resumen

The Data Science Model for the evaluation of clients of rural savings banks seeks to increase the credits granted to potential clients with or without a credit history and who possess or lack income and expense support. The evaluation consists of entering your identity document at the risk centers, measuring your income, expenses with or without supporting documents. Pilot tests were conducted in one of the agencies of the rural saving bank Edpyme Raiz for 3 weeks, obtaining favorable results and increasing from 10 to 30% the number of credits obtained per official when using the evaluation model and, if not, when the The result of the evaluation of the client is not favorable, it is suggested some recommendations to be able to approve again.

Idioma original	Inglés
Título de la publicación alojada	Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	329-334
Número de páginas	6
ISBN (versión digital)	9781728116914
DOI	https://doi.org/10.1109/IESTEC46403.2019.00067
Estado	Publicada - oct. 2019
Publicado de forma externa	Sí
Evento	7th International Engineering, Sciences and Technology Conference, IESTEC 2019 - Panama City, Panamá Duración: 9 oct. 2019 → 11 oct. 2019

Serie de la publicación

Nombre	Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019

Conferencia

Conferencia	7th International Engineering, Sciences and Technology Conference, IESTEC 2019
País/Territorio	Panamá
Ciudad	Panama City
Período	9/10/19 → 11/10/19

Nota bibliográfica

Publisher Copyright:
© 2019 IEEE.

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10.1109/IESTEC46403.2019.00067

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Gonzales, A. D. C., Villantoy, F. L. P., & Sanchez, D. S. M. (2019). Data science model for the evaluation of customers of rural savings banks without credit history. En Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019 (pp. 329-334). Artículo 8943666 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IESTEC46403.2019.00067

Gonzales, Aldo David Caceres ; Villantoy, Fabio Leonel Paucar ; Sanchez, David Santos Mauricio. / Data science model for the evaluation of customers of rural savings banks without credit history. Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 329-334 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019).

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title = "Data science model for the evaluation of customers of rural savings banks without credit history",

abstract = "The Data Science Model for the evaluation of clients of rural savings banks seeks to increase the credits granted to potential clients with or without a credit history and who possess or lack income and expense support. The evaluation consists of entering your identity document at the risk centers, measuring your income, expenses with or without supporting documents. Pilot tests were conducted in one of the agencies of the rural saving bank Edpyme Raiz for 3 weeks, obtaining favorable results and increasing from 10 to 30% the number of credits obtained per official when using the evaluation model and, if not, when the The result of the evaluation of the client is not favorable, it is suggested some recommendations to be able to approve again.",

keywords = "Credit history, Data analysis, Data science, Evaluation model, Payment capacity, Rural saving bank",

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Gonzales, ADC, Villantoy, FLP & Sanchez, DSM 2019, Data science model for the evaluation of customers of rural savings banks without credit history. En Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019., 8943666, Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 329-334, 7th International Engineering, Sciences and Technology Conference, IESTEC 2019, Panama City, Panamá, 9/10/19. https://doi.org/10.1109/IESTEC46403.2019.00067

Data science model for the evaluation of customers of rural savings banks without credit history. / Gonzales, Aldo David Caceres; Villantoy, Fabio Leonel Paucar; Sanchez, David Santos Mauricio.
Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 329-334 8943666 (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019).

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

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AB - The Data Science Model for the evaluation of clients of rural savings banks seeks to increase the credits granted to potential clients with or without a credit history and who possess or lack income and expense support. The evaluation consists of entering your identity document at the risk centers, measuring your income, expenses with or without supporting documents. Pilot tests were conducted in one of the agencies of the rural saving bank Edpyme Raiz for 3 weeks, obtaining favorable results and increasing from 10 to 30% the number of credits obtained per official when using the evaluation model and, if not, when the The result of the evaluation of the client is not favorable, it is suggested some recommendations to be able to approve again.

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KW - Data science

KW - Evaluation model

KW - Payment capacity

KW - Rural saving bank

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Gonzales ADC, Villantoy FLP, Sanchez DSM. Data science model for the evaluation of customers of rural savings banks without credit history. En Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 329-334. 8943666. (Proceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019). doi: 10.1109/IESTEC46403.2019.00067

Data science model for the evaluation of customers of rural savings banks without credit history

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