Equipped with strong problem-solving abilities, willingness to learn, and excellent communication skills. Poised to contribute to team success and achieve positive results. Ready to tackle new challenges and advance organizational objectives with dedication and enthusiasm.
· Analyses large-scale transactional data with Python (Pandas, Scikit-learn) to identify anomaly patterns and improve fraud detection models.
· Developed interactive compliance dashboards in Tableau to visualize high-risk transaction trends and merchant risk ratings for senior management.
· Prepared weekly and monthly compliance reports summarizing key risk indicators, suspicious activity volumes, and regulatory metrics.
· Conducted periodic back-testing of transaction monitoring rules and recommended threshold adjustments based on statistical analysis.
· Automated recurring data extraction and reporting tasks using SQL and Python, reducing manual effort by approximately 30%.
· Monitored daily transaction flows using SQL and Python to detect suspicious patterns and potential money laundering activities.
· Assisted in drafting and filing Suspicious Transaction Reports (STRs) in full compliance with MAS Notice 626 and the Payment Services (PS) Act.
· Conducted KYC and KYB due diligence reviews for merchant onboarding, ensuring 100% regulatory compliance.
· Reviewed and enhanced the rule-based AML transaction monitoring system, reducing false positive alerts by 18% while maintaining detection accuracy.
· Collaborated with product and technology teams to perform AML compliance assessments for new digital payment features prior to launch.