National and International Financial Market Regulation and Supervision Systems: Challenges and Solutions
Bibliographic record
Abstract
The purpose of this original study is to critically analyse the emergence and development of the national models of financial regulation, international standards and codes, and regional and national financial regulation and supervision (for the cases of the UK, USA, Sweden, the EU, and Finland). The research raises both academic and regulatory concerns. The relevance and purpose of this research arise from a need for an academic analysis of the economic nature and classification of financial market regulation systems. They represent a theoretical justification for changes in the policies and supervisory practices of national and international regulatory authorities in response to innovations in financial technologies and instruments, digital products, and risks. Secondly, it will stimulate more systematic work on regulatory databases, registration, and reporting procedures in various economies in different financial markets. The author identifies five main systems of national financial regulatory markets: the multi-tiered, multi-agency US system, the twin peaks model (UK), and the mega-regulatory model (Sweden). There is a thorough review of the international standards and institutions that work for the stability of financial systems. The analysis of the regional and national systems of financial regulation and supervision is based on the examples of the EU and Finnish institutions. National macro- and micro-economic regulation and supervision have been examined, with a focus on the US Federal Reserve and the US Treasury. An important result of the study is the systematisation of the directions of the development of national and international regulatory institutions (since the 1980s). First, the minimum capital and credit risk requirements for banks (the 1980s) were complemented in the 21st century by buffer reserves, liquidity, and leverage standards. Second, regulation focuses on ensuring the sustainability of the national economy. The regulatory focus is on ensuring the sustainability of national and global financial systems. Third, there is an increase in the number of supervised institutions. Fourth, there is a division of the functions between central banks (macro-economic regulation) and one or two mega-regulators (micro-economic regulation and supervision). Fifth, there is a division of labour between the international financial institutions (BIS, IMF, and WB) and national regulators. Sixth, the focus is on protecting consumers and investors and countering money laundering and the financing of terrorism. Seventh, there is an understanding based on a common approach by central banks to new financial technologies and cybersecurity.
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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 | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".