Revisiting the Impact of Mobile Banking in Financial Inclusion Among the Developing Countries
Bibliographic record
Abstract
Financial inclusion ensures financial products and services at reasonable rates for individuals and aims to introduce unbanked people into banking and financial services. The study aims to explore the effect that mobile banking facilities have on financial inclusion in 17 developing countries. From 2011 to 2017, this study took data from the three dimensions of financial inclusion called "Penetration," "Access," and "Uses". This paper took the Sarma model of Index of Financial Inclusion (IFI) to measure financial inclusion. This paper incorporates mobile money accounts as a "penetration" variable and Mobile banking outlet as an "Access" variable with existing model variables to quantify the effect of mobile banking. This research finds that mobile banking positively impacts the selected countries, though the degree of the changes is not symmetric. African regional countries have improved their financial inclusion after introducing mobile banking much better compared to other regions. This study is limited to examining mobile banking effects on selected emerging countries only. Future research may be devoted to developing more innovative strategies and tools to reach out to unbanked people, including people who face disparities in mobile phone ownership and bandwidth allocation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".