The future of global financial regulation
Bibliographic record
Abstract
The current architecture of financial regulation is out of step with the evolving global landscape of financial services. Global financial standards tend to respond to the prerogatives of advanced economies, but large developing countries play an increasingly important role as stakeholder and innovator in the global financial system. Moreover, even the world's poorest developing countries are deeply integrated into global finance, so decisions made in international standard-setting bodies have substantial implications for their economic development. We analyze regulatory developments in the areas of prudential banking, anti-money laundering, and shadow banking to show how global financial standards are essential and well-intended, but entail negative repercussions for inclusive growth in developing countries. In our outlook for the future of global financial regulation, we advocate for sustained global coordination and propose three specific reforms: First, standard setters move away from an exclusive focus on financial stability to the pursuit of the twin goals of financial stability and inclusive economic development - the equivalent of a Taylor rule for financial regulation. Second, reforms should be geared towards greater formal representation for developing countries. And third, we propose the transformation of an existing regulatory institution into a standard-setting body for fintech.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".