Increasing Digital Activity and Billing in a Banking Entity using Machine Learning
DOI:
https://doi.org/10.18687/LACCEI2025.1.1.716Keywords:
Machine Learning, Banking, Supervised ModelsAbstract
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.Downloads
Published
2025-04-09
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Copyright (c) 2025 LACCEI

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
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