Abhishek Pati
Vice President (Financial Crimes Analytics and Data Science) @Citi
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WORK HISTORY
Vice President (Financial Crimes Analytics and Data Science) @Citi
Tampa, FL, US
Focused on developing innovative ML techniques to identify suspicious activity and enhance existing operations.• Led the Behavior AI/ML Analytics team to develop advanced quantitative solutions and predictive models for AML using decision tree, logistic regression, random forest, etc.• Independently conducted tuning (Above the Line Analysis/Below the Line Testing/Sampling) and calibration for AML models which significantly reduced the number of false positive alerts with minimal risk to the bank.• Performed the annual reviews leading by Model Risk Management, OCC and FRB and ensure executive committees and regulators are apprised of progress against established milestones and action plans.• Coordinate and collaborate with partner teams (Compliance/AML Detection/Fraud) and model vendors to ensure a ‘forward thinking’ approach to the evolution of financial crimes initiatives, in response to regulatory requests to enhance the firm’s global transaction monitoring coverage and increase the effectiveness of the financial crimes program.• Responsible for hiring talents and providing leadership and mentorship for analysts.
EDUCATION
University of South Florida
Master's Degree, Management Information Systems and Services
University of South Florida
Master's degree, Management Information Systems, General
Kalinga Institute of Industrial Technology , Bhubaneswar , India
Bachelor's Degree, Engineering
SKILLS
ABOUT ABHISHEK PATI
At Citi, leadership in financial crimes analytics is demonstrated through pioneering machine learning solutions aimed at detecting and preventing illicit activities. In the role of Vice President, the focus has been on enhancing the bank\'s robustness against money laundering threats, using decision trees, logistic regression, and random forests to refine predictive models.Our team\'s efforts in Behavior AI/ML Analytics have significantly cut down false positive alerts, balancing risk and operational efficiency. The collaboration with Model Risk Management and regulatory bodies ensures that strategic milestones are met, showcasing a commitment to excellence and a secure financial environment.
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