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Know your data: Improving an anti-money laundering programme with dedicated data management
Journal of Financial Compliance,
5
(1),
45-54
(2021)
Abstract
Data is gathered, stored and analysed across the globe in every size business and industry faster than it ever has been at any point in human history; the velocity of data at a financial institution is no different. A financial institution’s anti-money laundering (AML) programme needs to equip itself to use this data to their advantage. A dedicated team must be formed to gather critical data for the programme. This team should focus on storing, mapping, evaluating and remediating the programme’s required data. This team can strengthen an AML programme’s base of data and information and, in turn, help the programme effectively and efficiently manage risk. With this base of quality data, the programme can tackle more advanced analytical tasks and use data to drive decision-making, ultimately leading to an efficient, innovative and compliant programme that helps it accomplish its primary job, identifying potential bad actors in the financial system.
Keywords: AML; data management; data quality; data issues; analytics; data advocate; data model
The full article is available to subscribers to the journal.
Author's Biography
Drew Galow has over 15 years of experience in the financial services industry in the areas of analytics, risk and compliance matters, with responsibility over the related data and technology. He currently serves as the Director of Anti-Money Laundering (AML) Model Development and Machine Learning for the Bank of Montreal, leading the bank’s AML monitoring efforts for Transaction Monitoring and Watchlist Management in North America. His current focus is transforming the monitoring programme by implementing advanced analytics and machine learning to continue to meet regulatory compliance and monitoring requirements for AML, anti-terrorist financing and Bank Secrecy Act obligations. He has a history of applying data analytics to increase profitability through marketing and to aid in strategic decision-making in legal compliance. He also has significant experience in developing and executing model development frameworks and projects related to AML technology and monitoring. He is a Certified Anti-Money Laundering Specialist (CAMS) and holds an undergraduate degree in Economics from the University of Wisconsin at Oshkosh. He earned a Master of Science degree in Data Science with an analytics and modelling specialisation from Northwestern University.
Sara Wright has over 20 years of experience in the financial services industry with a focus on data, technology, training and communication. She currently serves as the Director of AML Data Projects at Scotiabank, leading data governance efforts for pillars within the AML programme across Canada and international jurisdictions. She is currently instituting a data governance framework within Scotiabank’s AML programme, partnering with stakeholders and ensuring standards are met in service of regulatory milestones. She has a history of making technical subjects more easily understood and working with stakeholders to ensure communications are accurate. She also has experience in executing data-quality frameworks within an AML programme, guiding a team that performed data-quality assessments and provided monitoring outputs. She is a Certified Anti-Money Laundering Specialist (CAMS) and holds an undergraduate degree in Mass Communications from York University at Toronto and post-graduate certification in Technical Communications. In her spare time, she takes courses in data science, most recently with MIT and the University of Toronto.
