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Record W1809346817 · doi:10.5539/ass.v11n20p141

Assessment and Management of Banking Risks in the Global Community: Benefits and Challenges of Implementation of Basel Standards

2015· article· en· W1809346817 on OpenAlexvenueno aff
Kristina A. Kazakova, Alexander Knyazev, O. A. Lepekhin, Ella I. Skobleva

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEconomic and Technological Developments in Russia
Canadian institutionsnot available
Fundersnot available
KeywordsBasel IBasel IIOperational riskBusinessBasel IIIAccountingRisk managementRisk-weighted assetInternational bankingFinancial systemEconomicsFinanceCapital requirementMarket economyIncentive

Abstract

fetched live from OpenAlex

Regulation of banking risks by the state is due to the specifics of banking, associated with the transformation of deposits into loans and multiform negative effects that banking risks bear to the national economy. Since the late 1980s, the international practice of assessment and management of banking risks began to be reflected in the documents of the Basel Committee on Banking Supervision. In this paper we consider the evolution of Basel standards from Basel I to Basel III, and discuss substantial features of each generation of the standards. To date, a considerable number of countries, including Russia, have joined Basel standards. The paper discusses the features of regulation of banking risks in Russia, as well as the problems faced by commercial banks and the regulator in the implementation of Basel standards in the Russian banking sector.

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)0.047
metaresearch head score (Gemma)0.040
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: Empirical · Consensus signal: none
Teacher disagreement score0.047
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.040
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.008
Scholarly communication0.0130.009
Open science0.0010.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.150
GPT teacher head0.431
Teacher spread0.280 · 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
GenreEmpirical

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
Published2015
Admission routes1
Has abstractyes

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