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Growing Science » International Journal of Data and Network Science » Predictive models based on machine learning to analyze the adoption of digital payments in Latin America and the Caribbean

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International Journal of Data and Network Science

ISSN 2561-8156 (Online) - ISSN 2561-8148 (Print)
Quarterly Publication
Volume 9 Issue 3 pp. 411-418 , 2025

Predictive models based on machine learning to analyze the adoption of digital payments in Latin America and the Caribbean Pages 411-418 Right click to download the paper Download PDF

Authors: Jiang Wagner Mamani Lopez, Antonio Víctor Morales Gonzales, Pedro Pablo Chambi Condori

DOI: 10.5267/j.ijdns.2025.3.001

Keywords: Digital payments, Financial innovation, Data mining, Bayesian optimization, Hyperparameter Tuning

Abstract: The use of technology in the financial industry has experienced sustained growth in recent years. However, in many emerging economies, a significant proportion of the population still does not utilize digital solutions for financial transactions. Promoting financial inclusion through digital environments is essential for driving social and economic development. This study aims to develop machine learning models to predict the adoption of digital payments in Latin America and the Caribbean using statistical data from the World Bank's Global Findex Database for 2021. The performance of the Random Forest, LightGBM, XGBoost, and CatBoost algorithms was compared, with the optimal hyperparameter combination identified through Bayesian optimization. The results show that LightGBM achieved the highest performance in predicting digital payments, with an F1-score of 90.25% and a more stable balance between precision and recall compared to the other models. These findings highlight the value of machine learning models in the financial sector, as they enable a more accurate identification of users adopting digital solutions, facilitating the design of strategies to strengthen financial inclusion in the region.

How to cite this paper
Lopez, J., Gonzales, A & Condori, P. (2025). Predictive models based on machine learning to analyze the adoption of digital payments in Latin America and the Caribbean.International Journal of Data and Network Science, 9(3), 411-418.

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Journal: International Journal of Data and Network Science | Year: 2025 | Volume: 9 | Issue: 3 | Views: 226 | Reviews: 0

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