Financial Inclusion and the Role of Financial Literacy in the Philippines
Bibliographic record
Abstract
Financial inclusion is increasingly seen as a key enabler of various development objectives. While not explicitly one of the UN Sustainable Development Goals (SDGs), financial inclusion is recognized as an important enabler for them. The Philippine central bank—the Bangko Sentral ng Pilipinas (BSP)—has even identified financial inclusion as a “national development agenda” that requires a conscious effort by various sectors to accelerate and enable its societal benefits. This paper studies the relationship between financial literacy and financial inclusion in the Philippines using data gathered from the 2019 Financial Inclusion Survey (FIS). We apply ownership of financial account and use of financial services as indicators of financial inclusion. Based on the results, financial literacy is a positive driver of financial inclusion. We calculated that a one-standard-deviation increase in financial literacy scores increased the likelihood of holding at least one account by 3.7 to 4.2 percentage points. On the other hand, a one-point increase in financial literacy scores improved the likelihood of availing of a financial service by 4.9 to 6.0 percentage points. The other drivers of owning at least one formal account and availing of financial services are age, gender, employment status, awareness of BSP’s programs, income above 40,000 PHP, and being the main household financial decision-maker. This paper aims to promote BSP’s agenda to bridge the financial inclusion gap and raise financial literacy levels in the country. With this study, the authors second BSP’s advocacy that financial inclusion is one of the instruments to attain sustainable and equitable development in the Philippines.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".