| Autor: |
Howard Chitimira, Elfas Torerai, Lisa Jana |
| Jazyk: |
Afrikaans<br />German<br />English<br />Dutch; Flemish |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Potchefstroom Electronic Law Journal, Vol 27 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1727-3781 |
| DOI: |
10.17159/1727-3781/2024/v27i0a18024 |
| Popis: |
Abstract Money laundering and financial crimes pose a significant threat to the integrity and stability of South Africa’s financial system. This paper explores the application of artificial intelligence (AI) to detect and prevent money laundering in South African banking institutions. Through the implementation of big data technologies and data processing analytics, AI can enhance the detection and prevention of money laundering activities in South Africa’s banking sector. AI can be harnessed to improve the detection of suspicious activities, enhance accuracy of financial intelligence and adapt to evolving money laundering techniques. The paper 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 systems, regulatory compliance and ethical considerations. The paper further highlights the potential of AI in transaction monitoring, customer due diligence, outcomes-based risk assessment, and improved detection of suspicious transactions by analysing how AI can enhance the effectiveness and efficiency of AML measures. The importance of coordination between banking institutions, regulatory authorities and law enforcement bodies is also highlighted as an important component of leveraging AI to combat money laundering and related financial crimes in South Africa’s banking sector. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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