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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

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 originalInglés
Título de la publicación alojadaProceedings - 2019 7th International Engineering, Sciences and Technology Conference, IESTEC 2019
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas329-334
Número de páginas6
ISBN (versión digital)9781728116914
DOI
EstadoPublicada - oct 2019
Publicado de forma externa
Evento7th International Engineering, Sciences and Technology Conference, IESTEC 2019 - Panama City, Panamá
Duración: 9 oct 201911 oct 2019

Serie de la publicación

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

Conferencia

Conferencia7th International Engineering, Sciences and Technology Conference, IESTEC 2019
PaísPanamá
CiudadPanama City
Período9/10/1911/10/19

Huella Profundice en los temas de investigación de 'Data science model for the evaluation of customers of rural savings banks without credit history'. En conjunto forman una huella única.

Citar esto