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Tackling Money Laundering Through the Use of Data Analytics in Sierra Leone
(D349)
164
Points
Submitted:
Dec 19 2019
Status: 
Submitted

Government of Sierra Leone has intensified the fight to make corruption a high risk and low return venture especially by blocking pathways through which proceeds from corrupt activities can be utilised. One of such pathways is its anti-money-laundering drive which is led by the Financial Intelligence Unit.

The political will to tackle money laundering in Sierra Leone is being supported by the existing legal and regulatory framework. This includes the 'Anti-Money Laundering and Combating of Financing of Terrorism (AML/CFT) Act 2012' in Sierra Leone; the 'Terrorism Prevention (Freezing of International Terrorists Funds and other Related Measures) Regulations, 2013'; the 'Revised Directives for Financial Institutions on the prevention of Money Laundering and Terrorism Financing (2018)'; Resolutions from the United Nations Security Council and, several Memorandums of Understanding for information sharing with other entities in the anti-corruption and public financial management space.

Over the years, the day-to-day activities of Financial Intelligence Unit (FIU) depend heavily on the manual and semi-manual submission of different types of statutory reports including foreign, local currency, and suspicious transactions from various entities, processing of other requests for information (RFIs), and the analysis of this information to detect money laundering activities.

This process has been challenged by manual analytical processes, limited new technology to perform analysis of huge loads of data, lack of investment in the training of front-line staff in the FIU and reporting entities to detect signals of ML activities, non-existence or low use of investigative technology systems and incomplete coverage of data which is legally required to be reported.

In line with the National Innovation and Digital Strategy (NIDS), our Team will design, deploy and support the FIU in rolling-out a system capable of handling big financial data and beneficial ownership information. With the use of machine learning and artificial intelligence technologies, the FIU would be to able the use of data analytics and 'mining', anomaly detection and risk prediction methodologies to monitor the flows of particular transactions, determine the links between them and possible proceeds from corruption, money laundering and other crimes.

The system will be interoperable with the systems of other data sharing entities especially the Bank of Sierra Leone (the Central Bank), the National Revenue Authority (NRA), foreign exchange bureaus, the Anti Corruption Commission (ACC) and the Office of National Security (ONS). This sharing of information will facilitate the identification of suspicious persons, assets, criminal networks and associations, improve compliance and lower or prevent corruption and criminal incidents.

With potential funding and technical assistance through the International Monetary Fund's Innovation Lab, the Directorate of Science, Technology and Innovation (DSTI), and the Research and Delivery Division, Ministry of Finance (RDD-MOF) and Financial Intelligence Unit (FIU) will collaborate accordingly to support this initiative which aims to improve Sierra Leone's AML regulatory and compliance regime.

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