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Implementation of an effective and efficient anti-money laundering & counter terrorism financing system: the adoption of a behaviorally view
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| 3.3 MB | Adobe PDF |
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Resumo(s)
Money laundering and the financing of terrorism has been and is increasingly becoming an even greater concern for governments and for the operating institutions. The present document describes the activities partaken by the trainee, during his one-year internship at the Millennium BCP’s Compliance Office. The trainee first started with an integration/training period, having meetings and lectures with representatives and specialists of the multiple Compliance Office departments, on their duties and respective department role on the overall Compliance Office’s schema. An e-learning component was also complied, whereas the trainee had access to a battery of mandatory courses on legal and internal operation regulations, with both learning and evaluation modules. The trainee was then integrated in the Information Systems and Analytics Department’s team, and in its AML/CFT System implementation project. Once integrated, the trainee did some data analysis to the bank’s customer database, to uncover discrepancies and inconsistences, further providing possible solutions to correct these, in order to prepare for the AML/CFT system implementation. Relative to the implementation of the AML/CFT system, the trainee participated in the whole implementation and configuration process: the ETL process; the parametrization, definition and analysis of the system; The development, definition and calibration of detection algorithms on transactions suspicious of Money Laundering and/or Terrorism Financing; the preparation/adjustment of the decision algorithms according with the evaluation algorithms' assessments; The statistical assessment on the transactions and decisions made in accordance with the reintegration on the previous decision models; And the transactional behavior analysis.
Descrição
Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics
Palavras-chave
AML/CFT Analysis Segmentation Clustering Customer Due Diligence Risk Factor Machine Learning Compliance