Prediction of financial product acquisition for Peruvian savings and credit associations

Emmanuel Roque Vargas, Ricardo Cadillo Montesinos, David Mauricio

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

Resumen

Savings and credit cooperatives in Peru are of great importance for their participation in the economy, reaching in 2019, deposits and deposits and assets of more than 2,890,191,000. However, they do not invest in predictive technologies to identify customers with a higher probability of purchasing a financial product, making marketing campaigns unproductive. In this work, a model based on machine learning is proposed to identify the clients who are most likely to acquire a financial product for Peruvian savings and credit cooperatives. The model was implemented using IBM SPSS Modeler for predictive analysis and tests were performed on 40,000 records on 10,000 clients, obtaining 91.25% accuracy on data not used in training.

Idioma originalInglés
Título de la publicación alojada2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings
EditoresMonica Andrea Rico Martinez
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728194660
DOI
EstadoPublicada - 30 sep 2020
Evento2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - 2020 International Conference on Innovation and Trends in Engineering, CONIITI 2020 - Bogota, Colombia
Duración: 30 sep 20202 oct 2020

Serie de la publicación

Nombre2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings

Conferencia

Conferencia2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - 2020 International Conference on Innovation and Trends in Engineering, CONIITI 2020
País/TerritorioColombia
CiudadBogota
Período30/09/202/10/20

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© 2020 IEEE.

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