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Are the old ways of transaction monitoring dead?
Journal of Financial Compliance,
8
(2),
102-111
(2024)
Abstract
Financial institutions continue to face the challenge of demonstrating a comprehensive anti-money laundering (AML) transaction monitoring programme that is designed to detect, and aligns with, relevant Federal Financial Institutions Examinations Council (FFIEC) red flags without explicit, consistent confirmation on whether the escalations (ie Suspicious Activity Report [SAR] filings) are correct or valuable. Historically, this led most banks to adopt the use of typology-based if/then rules, resulting in a significant volume of alerts to be reviewed and dispositioned, with only a small portion being identified as potentially suspicious. While machine learning models are touted as an obvious fix to this problem, many banks may find such solutions to be far too expensive, complex and/or resource intensive. In order to answer the question, ‘are the old ways of transaction monitoring dead?’, this paper offers and evaluates various practical solutions, ranging from simple to sophisticated, to reduce false positive alerts generated by traditional AML transaction monitoring applications.
Keywords: transaction monitoring; machine learning; suspicious activity; false positive; rules-based; prioritisation; data quality
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Author's Biography
Carrie Gilson is Director of the Financial Intelligence Unit (FIU) at U.S. Bank and has oversight responsibility for model development, analysis and surveillance of transactional and customer data relevant to the identification of unusual activity. The FIU also manages data streams for transaction monitoring and sanctions screening, conducts threshold tuning for anti-money laundering (AML) and sanctions alert generation and provides innovative risk mitigation solutions through advanced analytics, modelling, data visualisation and automation. Prior to joining U.S. Bank in 2021, Carrie spent over 20 years at other financial institutions (JPMorgan Chase and KeyBank) with a specialised focus on financial crimes compliance and analytics. She previously managed teams to support AML, sanctions, know your customer, and fraud programmes with responsibilities including model development, defining coverage strategies and managing remediation activities. On a regular basis, Carrie participates in industry panel discussions and working groups focused on the advancement of transaction monitoring techniques and the practical application of emerging technologies in the compliance space. Carrie holds an MBA from the Kellogg School of Management at Northwestern University and a BS in decision sciences from Miami University in Ohio.
