Prediction of financial product acquisition for Peruvian savings and credit associations

Emmanuel Roque Vargas; Ricardo Cadillo Montesinos; David Mauricio

doi:10.1109/CONIITI51147.2020.9240413

Prediction of financial product acquisition for Peruvian savings and credit associations

Emmanuel Roque Vargas, Ricardo Cadillo Montesinos, David Mauricio

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings
Editors	Monica Andrea Rico Martinez
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728194660
DOIs	https://doi.org/10.1109/CONIITI51147.2020.9240413
State	Published - 30 Sep 2020
Event	2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - 2020 International Conference on Innovation and Trends in Engineering, CONIITI 2020 - Bogota, Colombia Duration: 30 Sep 2020 → 2 Oct 2020

Publication series

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

Conference

Conference	2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - 2020 International Conference on Innovation and Trends in Engineering, CONIITI 2020
Country/Territory	Colombia
City	Bogota
Period	30/09/20 → 2/10/20

Bibliographical note

Funding Information:
The authors would like to thank the Peruvian University of Applied Sciences for the partial funding of this research.

Publisher Copyright:
© 2020 IEEE.

Keywords

C4.5
KDD
SPSS
association of savings and credits
data mining
marketing

Access to Document

10.1109/CONIITI51147.2020.9240413

Cite this

Vargas, E. R., Cadillo Montesinos, R., & Mauricio, D. (2020). Prediction of financial product acquisition for Peruvian savings and credit associations. In M. A. R. Martinez (Ed.), 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings Article 9240413 (2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONIITI51147.2020.9240413

Vargas, Emmanuel Roque ; Cadillo Montesinos, Ricardo ; Mauricio, David. / Prediction of financial product acquisition for Peruvian savings and credit associations. 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings. editor / Monica Andrea Rico Martinez. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings).

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abstract = "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.",

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Vargas, ER, Cadillo Montesinos, R & Mauricio, D 2020, Prediction of financial product acquisition for Peruvian savings and credit associations. in MAR Martinez (ed.), 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings., 9240413, 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - 2020 International Conference on Innovation and Trends in Engineering, CONIITI 2020, Bogota, Colombia, 30/09/20. https://doi.org/10.1109/CONIITI51147.2020.9240413

Prediction of financial product acquisition for Peruvian savings and credit associations. / Vargas, Emmanuel Roque; Cadillo Montesinos, Ricardo; Mauricio, David.
2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings. ed. / Monica Andrea Rico Martinez. Institute of Electrical and Electronics Engineers Inc., 2020. 9240413 (2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Vargas, Emmanuel Roque

AU - Cadillo Montesinos, Ricardo

AU - Mauricio, David

PY - 2020/9/30

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N2 - 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.

AB - 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.

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ER -

Vargas ER, Cadillo Montesinos R, Mauricio D. Prediction of financial product acquisition for Peruvian savings and credit associations. In Martinez MAR, editor, 2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9240413. (2020 Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2020 - Conference Proceedings). doi: 10.1109/CONIITI51147.2020.9240413

Prediction of financial product acquisition for Peruvian savings and credit associations

Abstract

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Bibliographical note

Keywords

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