Increasing Digital Activity and Billing in a Banking Entity using Machine Learning
DOI:
https://doi.org/10.18687/LACCEI2025.1.1.716Palabras clave:
Machine Learning, Banking, Supervised ModelsResumen
This report describes a project in which Machine Learning technology is used to predict the propensity for e-commerce consumption of a banking entity's customers. The objective of the project is to increase two key business indicators: the percentage of clients who consume digitally in the month and billing, that is, the total amount consumed by clients; To this end, Machine Learning models were developed to predict which customers are the most prone to e-commerce consumption and which are the least prone, thus enabling the business to use this valuable information to redesign, improve and optimize its products. incentive strategies and launch campaigns to clients.Descargas
Publicado
2025-04-09
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Articles
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Derechos de autor 2025 LACCEI

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial 4.0.
Cómo citar
Diestra, J., & Carbajal, E. (2025). Increasing Digital Activity and Billing in a Banking Entity using Machine Learning. LACCEI, 1(12). https://doi.org/10.18687/LACCEI2025.1.1.716