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Record W4392931044 · doi:10.4236/jfrm.2024.131007

A Survey of Literature on Suspicious Transaction Monitoring: Anti-Money Laundering Compliance and Financial Performance of Commercial Banks in South Sudan

2024· article· en· W4392931044 on OpenAlexaff
Abraham Telar Nicknora

Bibliographic record

VenueJournal of Financial Risk Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMoney launderingDatabase transactionCompliance (psychology)BusinessFinancial transactionAccountingFinancial systemFinanceComputer scienceDatabasePsychology

Abstract

fetched live from OpenAlex

This research delves into the nexus between anti-money laundering (AML) compliance and the financial performance of selected commercial banks in South Sudan, a country still on the FATF grey list despite substantial governmental investments in AML initiatives. Utilizing a cross-sectional and mixed-method design, the study specifically aimed to scrutinize the relationship between internal policies and the financial performance of commercial banks. Drawing from a sample of 105 participants across four banks, a comprehensive dataset comprising both quantitative and qualitative information was gathered. The findings underscore a noteworthy connection between internal policies and financial performance (r = 0.436, p = 0.000, n = 86), suggesting that improvements in internal policies may enhance financial outcomes. This study emphasizes the pivotal role of robust internal policies in fostering AML compliance and subsequently enhancing the financial well-being of commercial banks in South Sudan.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.247
Teacher spread0.222 · 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 teacher head, not a consensus.

Study designObservational
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

Citations1
Published2024
Admission routes1
Has abstractyes

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