Prediction of financial product acquisition for Peruvian savings and credit associations
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Fecha de publicación
2020-09-30
Metadatos
Mostrar el registro completo del ítemJournal
2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference ProceedingsDOI
10.1109/CONIITI51147.2020.9240413Enlaces adicionales
https://ieeexplore.ieee.org/document/9240413Resumen
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.Tipo
info:eu-repo/semantics/articleDerechos
info:eu-repo/semantics/embargoedAccessIdioma
engDescripción
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.ae974a485f413a2113503eed53cd6c53
10.1109/CONIITI51147.2020.9240413
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