Previous Article in Journal
Uncovering Systemic Risk in ASEAN Corporations: A Framework Based on Graph Theory and Hidden Models
Previous Article in Special Issue
Inter-Market Mean and Volatility Spillover Dynamics Between Cryptocurrencies and an Emerging Stock Market: Evidence from Thailand and Sectoral Analysis
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

The Role of Digital Financial Services in Narrowing the Gender Gap in Low–Middle-Income Economies: A Bayesian Machine Learning Approach

by
Alicia Fernanda Galindo-Manrique
* and
Nuria Patricia Rojas-Vargas
Acounting and Finance Academic Department, Tecnologico de Monterrey, Monterrey 64700, Mexico
*
Author to whom correspondence should be addressed.
Risks 2025, 13(5), 96; https://doi.org/10.3390/risks13050096
Submission received: 16 March 2025 / Revised: 15 April 2025 / Accepted: 22 April 2025 / Published: 14 May 2025

Abstract

Women in emerging economies face unique constraints rooted in cultural norms, socio-economic disparities, and limited access to education and technology. Narrowing the digital gender gap by ensuring access to financial services may reduce the economic inequalities for women in these countries. This study examines the influence of digital finance in narrowing the gender gap, guided by the research question: To what extent do digital financial services contribute to narrowing the gender gap in access to and usage of financial services in low-and middle-income economies? Gender inclusion was measured by the ratio of accounts owned by women over the total number of accounts. Digital financial inclusion was constructed based on eight components: mobile money account, storing money in financial institutions, Internet access, mobile phone owned, savings, savings in financial institutions, making or receiving a digital payment, and mobile phone or use of the Internet for shopping. A Bayesian regression approach was computed using the Global Findex Database data for 73 countries classified as low and lower-middle-income economies from 2011 to 2022. The Machine Learning approach evaluates the model’s ability to predict women’s autonomy and the role of digital finance. The results show that digital financial services would reduce the gender gap in low-income economies while augmenting the number of open accounts, especially for women. The results aid in the establishment of policies to reduce the gender gap. These results are relevant to the UNSDG agenda, mainly Goal 5 and Goal 10.
Keywords: digital financial services; financial inclusion; gender equity; emerging economies digital financial services; financial inclusion; gender equity; emerging economies

Share and Cite

MDPI and ACS Style

Galindo-Manrique, A.F.; Rojas-Vargas, N.P. The Role of Digital Financial Services in Narrowing the Gender Gap in Low–Middle-Income Economies: A Bayesian Machine Learning Approach. Risks 2025, 13, 96. https://doi.org/10.3390/risks13050096

AMA Style

Galindo-Manrique AF, Rojas-Vargas NP. The Role of Digital Financial Services in Narrowing the Gender Gap in Low–Middle-Income Economies: A Bayesian Machine Learning Approach. Risks. 2025; 13(5):96. https://doi.org/10.3390/risks13050096

Chicago/Turabian Style

Galindo-Manrique, Alicia Fernanda, and Nuria Patricia Rojas-Vargas. 2025. "The Role of Digital Financial Services in Narrowing the Gender Gap in Low–Middle-Income Economies: A Bayesian Machine Learning Approach" Risks 13, no. 5: 96. https://doi.org/10.3390/risks13050096

APA Style

Galindo-Manrique, A. F., & Rojas-Vargas, N. P. (2025). The Role of Digital Financial Services in Narrowing the Gender Gap in Low–Middle-Income Economies: A Bayesian Machine Learning Approach. Risks, 13(5), 96. https://doi.org/10.3390/risks13050096

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop