Using Artificial Intelligence to Combat Money Laundering

Alhajeri, Rashid; Alhashem, Abdulrahman

doi:10.4236/iim.2023.154014

Cited by 4 publications

(1 citation statement)

References 31 publications

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“…Additionally, the engine can use artificial intelligence (AI) to classify each transaction as either normal or suspicious. Furthermore, a transaction classified as suspicious is expected to raise an alert which is to be reviewed by a human who will confirm or block the transaction and submit the blocked transactions to the respective authorities for further procedures and investigations (19) , (20) .…”

Section: User Identification Privacy and Data Protection Laws And Reg...mentioning

confidence: 99%

Database Privacy: Design of User Privacy Preserving Central Bank Digital Currency: A Case of Tanzania

Minja,

Nyambo,

Sam

2024

IJST

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Objectives: This work aims to contribute towards Tanzanian Central Bank Digital Currency (CBDC) users’ privacy preservation. It proposes the design of a privacy preserving CBDC which might be issued by Tanzania's Central Bank (CB), the Bank of Tanzania (BoT), which is currently in CBDC research phase. The work also aims to contribute to literature, the CBDC research being done by BoT, other CBs and CBDC stakeholders around the world. Methods: By using the Design Science Research (DSR) methodology, a privacy preserving CBDC design suitable for Tanzania was proposed, demonstrated and evaluated. This is the result of existing literature showing that different countries have different CBDC designs due to their differences in contexts and purposes for CBDC issuance. This consequently emphasized the fact that a CBDC design should not be treated as a one-size fits all solution. Findings: As opposed to the existing general and other country specific CBDC designs, we proposed a privacy preserving CBDC design suitable for Tanzania by consulting literature and taking into consideration the Tanzanian context. The design appears to be promising Tanzanian CBDC users’ privacy preservation though further work needs to be done. The work should not only be on practical evaluation of the proposed design but also on other factors impacting the success of CBDC projects. This will consequently further increase the success probability of CBDC projects, hence the potential for practical realization of CBDC project benefits. Novelty: Existing literature has shown that, considering the countries’ differences in context and CBDC issuance purposes, CBDC design should not be treated as a generic solution thereby obliging the need for country-specific CBDC designs. Consequently, the privacy preserving CBDC design suitable specifically for Tanzania consists of and provides an outline of privacy preserving interactions among the identified key Tanzanian CBDC participants or actors. The actors are the BoT, the intermediaries (i.e., other banks and payment service providers), Tanzania’s National Identification Authority (NIDA), financial transactions violation detection engine, and the expected CBDC users. Keywords: Digital currency, database privacy, central bank digital currency, privacy

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Section: User Identification Privacy and Data Protection Laws And Reg...mentioning

confidence: 99%

Database Privacy: Design of User Privacy Preserving Central Bank Digital Currency: A Case of Tanzania

Minja,

Nyambo,

Sam

2024

IJST

View full text Add to dashboard Cite

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Leveraging Artificial Intelligence to Combat Money Laundering and Related Crimes in the South African Banking Sector

Chitimira,

Torerai,

Jana

2024

PER

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Money laundering and related financial crimes, such as fraud and terrorism financing, pose a significant threat to the integrity and stability of South African financial markets. This article explores the application and use of artificial intelligence (AI) to detect and prevent money laundering in South African banking institutions. The implementation of big data technologies, data processing analytics and AI could enhance the detection and prevention of money laundering activities in South Africa's banking sector. AI should be carefully utilised to improve the detection of suspicious activities and the accuracy of financial intelligence, and to combat evolving money laundering techniques. The article also examines the benefits and challenges of implementing AI as an anti-money laundering (AML) measure in the South African banking sector. These include the need for quality data, integration with existing regulatory systems, regulatory compliance and ethical considerations. The article highlights the potential use of AI in transaction monitoring, customer due diligence, outcomes-based risk assessment and the improved detection of suspicious transactions. This could be done by utilising AI to enhance the effectiveness and efficiency of AML measures. The importance of effective coordination between banking institutions, regulatory authorities and law enforcement bodies is also highlighted as a key component of leveraging AI to combat money laundering and related financial crimes in South Africa's banking sector.

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Financial Monitoring Through Artificial Intelligence: Strategies for Preventing Financial Crimes in Dynamic Markets

Utkina,

Bondarenko

2024

Preprint

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Using Artificial Intelligence to Combat Money Laundering

Cited by 4 publications

References 31 publications

Database Privacy: Design of User Privacy Preserving Central Bank Digital Currency: A Case of Tanzania

Database Privacy: Design of User Privacy Preserving Central Bank Digital Currency: A Case of Tanzania

Leveraging Artificial Intelligence to Combat Money Laundering and Related Crimes in the South African Banking Sector

Financial Monitoring Through Artificial Intelligence: Strategies for Preventing Financial Crimes in Dynamic Markets

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