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Record W2994914224

Іноземний досвід регулювання системно важливих банків

2019· article· en· W2994914224 on OpenAlexaboutno aff
Владислав Володимирович Лавренюк, Vladyslav Lavreniuk

Bibliographic record

VenueInstitutional Repository of Vadym Hetman Kyiv National Economic University iRKNEU (Kyiv National Economic University named after Vadym Hetman) · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The article considers methodological approaches and practical aspects of \nidentification and regulation of systemically important banks at the national and \nthe global levels. The article contains thorough overview of the Basel principles for \nidentification and building a system for regulation of activities of the systemically \nimportant banks at the global level. The author gives a list of the main documents of \nthe Basel Committee regarding matters related to the identification and regulation of \nthe systemically important banks. The research gives a list of the global systemically \nimportant banks identified by the Basel Committee and the Financial Stability \nBoard. The article discloses the additional requirements for equity for supplemental \ncoverage of bank losses being identified by the Basel Committee and the Financial \nStability Board as the global systemically important ones. The global systemically \nimportant banks identified by the Basel Committee and the Financial Stability \nBoard have been analyzed in the context of regional distribution. \nThe article presents the main categories of the system importance proposed by the \nBasel Committee for conducting a procedure of identification of the global systemically \nimportant banks. The article describes fundamental principles for dealing with the \nnational systemically important banks proposed by the Basel Committee. The author \nhas thoroughly analyzed the methods for identification of the national systemically \nimportant banks in various countries of the world, namely the USA, Canada, Germany, \nSweden, the Netherlands, the Czech Republic, Denmark, India, and Australia. The \nresearcher has taken into account advantages and disadvantages of the methods for \nidentification of the systemically important banks of various countries. The article \ncontains basic aspects of building the system for regulation of activities of the \nsystemically important banks in the Netherlands, Germany, Denmark, and Canada. \nThe done analysis of the foreign experience related to the identification and \nregulation of the national systemically important banks has enabled to indicate \na list of key decisions regarding the regulation of activities of these banks in \nvarious countries of the world. Concluding the results of analysis of the foreign \nexperience related to the identification and regulation of the national systemically \nimportant banks, the author proposes recommendations on improvement of the \nidentification and regulation of activities of the national systemically important \nbanks in the banking system of Ukraine.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.004

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.

Opus teacher head0.011
GPT teacher head0.186
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

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