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Record W2999449329 · doi:10.1108/jmlc-04-2019-0033

State and institutional capacity in combating money laundering and terrorism financing in armed conflict

2020· article· en· W2999449329 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Money Laundering Control · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMoney launderingTerrorismAutonomyGovernment (linguistics)FinanceState (computer science)BusinessProcurementLegislationFinancial systemEconomic policyEconomicsAccountingPolitical scienceLaw

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to explore the relationship and implications of institutional autonomy and capacity through the Central Bank of Syria in its ability to implement an effective anti-money laundering (AML) and counter-terrorism financing (CTF) framework during a period of intense armed conflict. Design/methodology/approach Due to the lack of reliable data currently available on Syria, this paper focuses on Syria’s AML/CTF legislation through passed laws and regulations; annual reports on the Central Bank of Syria and the AML and terrorism financing authority; the academic literature on money laundering, terrorist financing and institutional capacity. This paper will address the theoretical framework of Coleman and Skogstad’s characteristics that define the degree of autonomy and capacity of an institution. Though their characteristics are applied toward the Canadian state, for the purpose of this paper, they have been adopted in the absence of their use verbatim in the case of the Central Bank of Syria. Findings The Central Bank of Syria has experienced diminishing independence due to conflict-induced stress in Syria’s financial sector. This loss of autonomy is attributed to the prioritization of government-led emergency policies to secure and stabilize Syria's economy. Despite this loss, the Central Bank of Syria has maintained considerable and effective improvements in Syria’s AML/CTF framework, aligning it closer to that of international standards promoted by the Financial Action Task Force (FATF). Institutional gaps, however, still exist. These gaps imply that the Central Bank of Syria still lags in a number of areas that affect its capability in implementing a more effective AML/CTF framework. Research limitations/implications The conflict in Syria is still a very new topic that lacks a considerable amount of reliable data. As such, many research limitations were encountered despite the volume of information reviewed for this paper in both Arabic and English. Nevertheless, this paper provides a clearer understanding of how state capacity is reflected in its institutions through certain policies and approaches taken by a central monetary authority with implications and results in a country rattled by years of intense conflict. Practical implications Despite the research limitations and implications, this paper provides a clearer understanding of how state capacity is reflected in its institutions through certain policies and approaches taken by a central monetary authority with implications and results in a country rattled by years of intense conflict. This can be useful for institutional policymakers, as well as academics exploring the relationship between the state and its institutions in times of hardship. Originality/value Though there is AML/CTF literature on Middle Eastern countries such as Egypt, Jordan and Saudi Arabia, very little is written on Syria. There is also very little written on the broader subject of state and institutional capacity through the lens of an effective AML and CTF framework during a period of intense armed conflict. By looking at an ongoing conflict, this paper explores a subject with as much detail as needed to provide an illustration of the relationship and implications of institutional autonomy and capacity in relation to the state through an effective AML/CTF framework in a country with a struggling financial system.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.553
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.055
GPT teacher head0.267
Teacher spread0.213 · 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