Improving the mechanism of international cooperation in the field of identification, tracing and management of assets obtained from corruption and other crimes
Bibliographic record
Abstract
The article discusses the mechanism of international cooperation in the field of detection, tracing and management of assets derived from corruption and other crimes, and outlines the regulatory framework of the Institute for Combating Illicit Assets. The fight against illicit assets at the international level is based on the following key agreements and standards: The UN Convention against Corruption (UNCAC); the Council of Europe Convention on Laundering, Search, Seizure and Confiscation of the Proceeds from Crime; the StAR Initiative; and the FATF Recommendations. In Ukraine, the process of returning illegally acquired assets is regulated by a number of legal acts, including: The Criminal Procedure Code of Ukraine, the Law of Ukraine «On the National Agency for Finding, Tracing and Management of Assets Derived from Corruption and Other Crimes», and the Law of Ukraine «On Prevention and Counteraction to Legalization (Laundering) of the Proceeds of Crime». The positive experience of foreign countries in the field of identification, tracing and management of assets obtained from corruption and other crimes is highlighted. The powers of international bodies and the National Agency of Ukraine for Identification, Tracing and Management of Assets Obtained from Corruption and Other Crimes (ARMA) are compared. Attention is drawn to the fact that in international practice, countries such as the USA, Great Britain, Canada and France have bodies and mechanisms similar to Ukrainian ones, which not only coordinate internal measures to identify and manage illegally obtained assets, but also have expanded powers to launch international procedures for the return of these assets. The problems of the mechanisms for the return of illegally acquired property are analyzed and prospects for improving the mechanisms for the return of illegally acquired property are proposed, proposals are made for improving Ukrainian legislation in the field of identification, tracing and management of assets obtained from corruption and other crimes. To improve Ukrainian legislation in the field of the return of illegal assets, it is necessary to: consolidate at the legislative level the powers of ARMA to independently submit international requests for the seizure and return of assets; optimize the procedures for international interaction and expand cooperation with foreign financial institutions and law enforcement agencies; bring national legislation into line with international standards, in particular FATF recommendations and EU norms; introduce effective mechanisms for the prompt exchange of information between ARMA and international structures; strengthen international cooperation in the areas of tracing and return of assets. The article pays attention to improving the effectiveness of international cooperation in combating money laundering, analyzes the provisions of the draft Law № 12446 of 27.01.2025, outlines the challenges that arise in the practical activities of bodies whose activities are related to the identification, tracing and management of assets derived from corruption and other crimes, and emphasizes the importance of introducing effective legal mechanisms for asset recovery to combat corruption and economic crime.
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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 | 0.029 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".