Opportunities and Barriers for FinTech in SAARC and ASEAN Countries
Why this work is in the frame
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Bibliographic record
Abstract
This article assesses the opportunities and challenges for different categories of FinTechs in the SAARC and ASEAN regions. We consider the global financial inclusion data released by the World Bank and map the responses to gain insights into the opportunities and challenges for FinTechs in the respective regions. We develop a new index, termed the FinTech Opportunity Index (FOI), to conceptualise the opportunities and barriers based on individual savings, borrowings, purchasing behaviour, and payment preferences. We note that FinTech services have potential opportunities for expansion in the ASEAN regions but less so in the SAARC regions. The need for different types of FinTech services varies between regions. Services such as crowdfunding, neobanks, and InsurTech have potential in the ASEAN regions, especially with the positive attitude towards entrepreneurship and asset investments. In the SAARC regions, InsurTechs linked to health care has potential along with LendTechs and neobanks. We further note that males, and the young are more likely adopters of FinTechs in both regions. The analysis suggests the need for innovative promotions and education to motivate the more sceptical, especially women and the elderly population, to adopt FinTech services.
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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 | 0.001 | 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 it