The effect of digital finance on financial stability
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Digital finance plays a major role in achieving financial inclusion targets which have a positive impact on economic growth and people's welfare. One of the main elements of digital finance is digital payments, which are increasingly playing a role with the presence of e-commerce and financial technology (fintech). Apart from these positive impacts, digital finance is also feared to have a negative impact on financial system stability, especially in relation to systematic risk. The purpose of this study was to determine the role of risk factors in digital financial relations and financial stability. The research method used is the Multiple Linear Regression Model and Moderating Regression Analysis (MRA), using 120 samples of panel data for 10 years (2010 to 2019). The results show that market risk can moderate the influence of digital finance on financial stability, so that increased systematic risk will reduce the positive impact of digital finance on financial stability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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