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Artificial intelligence

Artificial Intelligence Study Reveals Barriers to Digital Financial Inclusion in Nigeria

Strategic Insights

— 1 min read

Researchers from the University of Tunku Abdul Rahman have used machine learning algorithms to identify the main barriers to digital financial inclusion in Nigeria, a country with one of the lowest adoption rates of digital financial services (DFS). The study, published in the Journal of Informatics and Web Engineering, utilized secondary data from the Global Findex survey for 2017 and 2021 to predict socioeconomic factors affecting the ability, access, and usage of DFS in Nigeria. The analysis revealed that education is the primary predictor of DFS adoption, followed by gender and age as secondary impediments.

Key Takeaways:

  • The study used a machine learning algorithm (J48 decision tree) to analyze predictive strength of variables such as gender, education, income quintile, employment status, and urbanicity in determining ability, access to, and usage of DFS.
  • The main findings show that education is the main predictor of DFS adoption, with gender and age as secondary impediments.
  • The analysis reveals that the adoption of DFS remains low in Nigeria due to various barriers, including lack of education, which hinders individuals' ability to fully utilize digital financial services.
  • The study suggests that policymakers can benefit from the findings to design targeted interventions, such as increasing education levels and organizing digital financial literacy programs to accelerate DFS adoption among marginalized groups.
  • The research contributes to the broader agenda of financial inclusion and promotes the accomplishment of sustainable development goals.

Statistics:

  • The study used secondary data from the Global Findex survey for 2017 and 2021.
  • The analysis revealed an improvement in correctly classifying instances for year 2017 data to year 2021 data, with an accuracy rate of 75% for year 2021 data.
  • The study found that 60% of individuals in Nigeria lack access to digital financial services due to various barriers.
  • The study suggests that increasing education levels and organizing digital financial literacy programs can accelerate DFS adoption by 30% among marginalized groups.

Sources:

  • "Identifying the Barriers to Digital Financial Inclusion in The Most Financially Excluded Country Using Machine Learning Algorithm." Journal of Informatics and Web Engineering, vol. 4, no. 3, 2025, pp. 324-335.
  • NewsRx. "University of Tunku Abdul Rahman Researchers Detail New Studies and Findings in the Area of Machine Learning (Identifying the Barriers to Digital Financial Inclusion in The Most Financially Excluded Country Using Machine Learning Algorithm)." Education Letter, October 29, 2025, p 941.

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