Back

Speaker "Leah Mcfarland" Details Back

 

Topic

Moving beyond rules-based approaches in financial monitoring

Abstract

Rules-based approaches to conducting financial monitoring result in significant false positives (eg, 95%+) while potentially missing actual high risk. Most large financial institutions face significant data challenges related to legacy systems, poor data quality, missing data, and siloed data, which makes entity resolution (ie, recognizing every point the institution interacts with a given entity) difficult. New tools need to be leveraged to address these issues.
Who is this presentation for?
Anyone involved in conducting financial monitoring, or in transitioning from rules-based approaches to the use of machine learning
Prerequisite knowledge:
Familiarity with rules-based approaches to monitoring, esp. in the financial sector
What you'll learn?
Better approaches to conducting financial monitoring and leveraging available data

Profile

Leah McFarland has worked as a Director of Technical Program and Product Management at major U.S. banks, including JPMorgan Chase, State Street, and Citibank, where she has focused on data management, cloud migration, and the use of AI/ML and automation, with a specialty in financial monitoring issues.
 
Prior to that, Leah worked at FSVC, where she managed a $5 million portfolio delivering risk management assistance to financial institutions in the Middle East, North Africa, Sub-Saharan Africa, and Eastern Europe.
 
She began her career as a diplomat for the U.S. Department of State, serving in Moscow, the Secretary of State’s operations center in Washington, DC, and Sao Paulo.
 
Leah has an M.A. in International Affairs from the University of California at San Diego and speaks Spanish, Portuguese, Russian, French, and Mandarin.