Digital financial inclusion in Latin America: An application of classification models
DOI:
https://doi.org/10.18041/1900-3803/entramado.1.12332Keywords:
Financial inclusion, Latin America, Classification treesAbstract
Digital financial inclusion is crucial for economic and social development in Latin America, where access to basic financial services is limited and the informality in the economy has been reluctant to decrease. This paper uses a novel methodology for classified individuals according to whether or not they have a mobile account (also known as e-wallets) based on their socio-economic characteristics, the holding of other instruments, and the country of origin among four Latin American nations (Argentina, Brazil, Colombia, and Peru) in 2021. Mobile accounts fostered inclusive growth, reduced transaction costs and geographical constraints, and were boosted in the post-pandemic era. The objective is to identify the most relevant attributes of mobile account ownership to improve digital financial inclusion. For the classification, the results highlight age and income as relevant but also owning a debit card, accessing the Internet at home, and having saved in the last year as significant factors leaving behind the country of origin (meaning that they are very alike) or typically relevant attributes for traditional finance like education or gender.
Downloads
References
Agufa Midika, M. (2016). The Effect of Digital Finance on Financial Inclusion in The Banking Industry in Kenya, Doctoral dissertation, University Of Nairobi, Nov. 2016.
Asongu, S. A., Biekpe, N., & Cassimon, D. (2021). On the diffusion of mobile phone innovations for financial inclusion. Technol. Soc., 65, 101542.
Aziz, A., & Naima, U. (2021). Rethinking digital financial inclusion: Evidence from Bangladesh. Technology in Society, 64, 101509.
Bastante, M. (2020). Estudio Fintech 2020: Ecosistema Argentino. Banco Interamericano de Desarrollo. Nota Técnica Nº IDB-TN-2070.
Breiman, L., Friedman, J., Olshen, R., & Stone, C. (1984). Classification and regression trees. New York: Routledge. doi: 10.1201/9781315139470.
Cantú, C., & Ulloa, B. (2020). The dawn of fintech in Latin America: landscape, prospects and challenges. Bank for International Settlements Papers, No 112.
Durica, M., Frnda, J., & Svabova, L. (2019). Decision tree based model of business failure prediction for Polish companies. Oeconomia Copernicana, 10(3), 453-469. doi: 10.24136/oc.2019.022.
ENIF (2020). Estrategia Nacional de Inclusión Financiera. Ministerio de la Nación. Argentina. Retrieved at: https://www.argentina.gob.ar/sites/default/files/enif_2020-23_vf _011220_con_prologo_1.pdf
Fungáčová, Z., & Weill, L. (2015). Understanding financial inclusion in China. China Economic Review, 34, 196-206.
Gomber, P., Koch, J. A., & Siering, M. (2017). Digital Finance and FinTech: current research and future research directions. Journal of Business Economics, 87, 537-580.
Ioannou, S., & Wójcik, D. (2022). The limits to FinTech unveiled by the financial geography of Latin America. Geoforum, 128, 57-67.
Kling, G., Pesqué-Cela, V., Tian, L., & Luo, D. (2022). A theory of financial inclusion and income inequality. The European Journal of Finance, 28(1), 137-157.
Levine, M. R. (2021). Finance, growth, and inequality. International Monetary Fund.
Lin, W., Ke, S., & Tsai, C. (2017). Top 10 data mining techniques in business applications: a brief survey. Kybernetes, 46(7). doi: 10.1108/k-10-2016-0302.
Martinez, L. B., Scherger, V., Guercio, M. B., & Orazi, S. (2020). Evolution of financial inclusion in Latin America. Academia Revista Latinoamericana de Administración, 33, 2.
Orazi, S., Martinez, L. B., & Vigier, H. (2023). Determinants and evolution of financial inclusion in Latin America: a demand side analysis. Quantitative Finance and Economics, 7(2), 187-206. DOI: 10.3934/QFE.2023010
Ozili, P. K. (2018). Impact of digital finance on financial inclusion and stability. Borsa Istanbul Review, 18(4), 329-340.
Parvin, S. R., & Panakaje, N. (2022). A study on the prospects and challenges of digital financial Inclusion. International Journal of Case Studies in Business, IT and Education (IJCSBE), 6(2), 469-480
Piotrowska, A. I. (2024). Determinants of consumer adoption of biometric technologies in mobile financial applications. Economics and Business Review, 10(1), 81-100.
Prusak, B. (2018). Review of research into enterprise bankruptcy prediction in selected central and eastern European countries. International Journal of Financial Studies, 6(3). doi: 10.3390/ijfs6030060.
Sharma, A., & Kukreja, S. (2013). An analytical study: Relevance of financial inclusion for developing nations. International journal of engineering and science, 2(6), 15-20.
Tay, L. Y., Tai, H. T., & Tan, G. S. (2022). Digital financial inclusion: A gateway to sustainable development. Heliyon, 8(2022). doi.org/10.1016/j.heliyon.2022.e09766.
Tram, T. X. H., Lai, T. D., & Nguyen, T. T. H. (2021). Constructing a composite financial inclusion index for developing economies. Q. Rev. Econ. Finance, 1-9.
World Bank, Digital Financial Inclusion, 2021. Available Online: https://www.worldbank.org/en/topic/financialinclusion/publication/digital-financial-inclusion
Yangdol, R., & Sarma, M. (2019). Demand-side factors for financial inclusion: A cross-country empirical analysis. International Studies, 56, 163–185.
Zins, A., & Weill, L. (2016). The determinants of financial inclusion in Africa. Review of development finance, 6(1), 46-57.
Published
Issue
Section
License
Copyright (c) 2025 Entramado

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.