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Features of public influence on the functioning of the financial leasing market: comparative legal analysis

2025· article· W4417253337 on OpenAlexaboutno aff
Dmutro Bagriychuk

Bibliographic record

VenueYearly journal of scientific articles “Pravova derzhava” · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicBanking, Crisis Management, COVID-19 Impact
Canadian institutionsnot available
Fundersnot available
KeywordsHarmonizationDirectiveLegislationTransparency (behavior)European unionFlexibility (engineering)Context (archaeology)LegislatureFinancial regulation

Abstract

fetched live from OpenAlex

Abstract. The article examines the peculiarities of public administration of the financial leasing market in Ukraine in the context of international experience and integration into the European legal space. The main focus is on the analysis of the administrative and legal regulation of the market, its regulatory framework, institutional architecture, as well as oversight and control mechanisms. The study highlights the problems of regulatory fragmentation, the absence of a single regulator, and the insufficient adaptation of national legislation to modern challenges, which limit the efficiency of market functioning and investment attractiveness. A comparative legal analysis of financial leasing regulation models in four key jurisdictions: the European Union (EU), the USA, Canada, and Japan, is carried out. The study emphasizes the advantages and disadvantages of each model. It is established that the European model is distinguished by the harmonization of regulatory standards and the provision of cross-border financial services, which contributes to increased transparency and simplified licensing. The American system is characterized by decentralization, flexibility in regulation, and innovative approaches to problem-solving. The Canadian model stands out for its adaptability to regional conditions, which allows for taking into account the specifics of different provinces, while the Japanese system is focused on long-term stability and predictability. Special attention is paid to the analysis of harmonized EU standards, which are based on directives, in particular MiFID II and Directive 2008/48/EC. Thanks to the "passporting" of financial services, the European model contributes to reducing barriers to entry for new market players and ensuring the unity of regulatory approaches. At the same time, the USA uses risk-based approaches, focusing on consumer protection and supporting innovative solutions, particularly in the field of financial technologies. The Canadian system demonstrates effectiveness in balancing centralized oversight and regional specifics, while the Japanese model ensures a high level of trust in financial institutions due to strict supervision and the implementation of corporate governance mechanisms. The article emphasizes the need to adapt Ukrainian legislation to European standards and implement best practices from other countries. The creation of a single regulator for the financial leasing market is proposed, which will ensure centralized licensing, monitoring, and oversight of market participants. The introduction of digitalization, the development of effective consumer protection mechanisms, and the application of risk-based approaches are also recommended as key steps to improve the regulatory system. Based on the conducted analysis, it is stated that the most promising approach for Ukraine is one that combines the harmonization of standards with the ability to adapt to national and regional conditions. This will allow for the creation of an effective, transparent, and sustainable model of public administration that will meet modern challenges and contribute to economic development. Key words: public administration, financial leasing, international experience, harmonization, digitalization, consumer protection, risk-based approaches.

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)0.006
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: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.004
Scholarly communication0.0050.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.047
GPT teacher head0.279
Teacher spread0.232 · 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
Published2025
Admission routes1
Has abstractyes

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