Leveraging Artificial Intelligence in Anti-Money Laundering

Speaker

Sarkis Mazraani

About The Speaker

Banking-Finance | Operational Risk | AML-CFT-CPF-AFC-Compliance | Governance Board Member | Fintech-Regtech-AI-Cybersecurity | GRC | Headed OpRisk & AML Lecturer-Consultant-Trainer-Specialist

Sarkis is a seasoned professional with extensive expertise in Banking, Governance, Compliance, Technology, and Regulatory Affairs, backed by over 20 years of progressive experience. He spent two decades at Standard Chartered Bank, specializing in Operational Risk Management, FinTech, RegTech, and Cybersecurity. His core competencies include Anti-Financial Crime (AFC), Anti-Money Laundering (AML), Combating the Financing of Terrorism (CFT), ISO implementation, Blockchain, Cryptocurrency, and Financial Services Compliance. He has a proven track record in ensuring compliance across both international and local banks.

Sarkis holds professional certifications from ACAMS, Grant Thornton, and the University of London. He is a recognized international conference speaker and facilitator, as well as an experienced trainer and coach in soft skills and management. Currently, Sarkis provides Governance, Risk Management, and Compliance (GRC) advisory, consultancy, training, lecturing, and coaching services—in both English and Arabic—across the Middle East, GCC, North Africa, Australia, and the USA.

Upcoming Event

Leveraging Artificial Intelligence in Anti-Money Laundering

  • 14th November, 2025
  • Online
  • 9AM to 12PM
  • Rs 9,000 (MQA approved & HRDC refundable up to 75%)
Register Now
Course Details

Overview

In today’s fast-paced regulatory environment, compliance officers and Money Laundering Reporting Officers (MLROs) face increasing complexity in monitoring, reporting, and preventing financial crimes. Artificial Intelligence (AI) offers transformative tools that can automate routine tasks, detect anomalies, enhance due diligence, and improve decision-making. By integrating AI into compliance workflows, institutions can increase operational efficiency, reduce risks, and strengthen regulatory adherence.

This workshop equips participants with the knowledge and practical skills to harness AI effectively, ensuring they remain ahead of evolving threats while meeting stringent compliance requirements. Attendees will explore real-world applications, ethical considerations, and future trends shaping AI-driven compliance strategies.

Course Objectives

  • Identify key AI technologies applicable to compliance and AML/CFT functions.
  • Demonstrate how AI can streamline transaction monitoring and risk assessment.
  • Apply AI-driven tools to enhance regulatory reporting and due diligence processes.
  • Evaluate the ethical and legal considerations of using AI in compliance work.

Profile of Participants

  • Compliance Officers
  • Money Laundering Reporting Officers (MLROs)
  • Risk Managers
  • Internal Auditors
  • AML/CFT Analysts
  • Financial Crime Investigators

Course Outline

Overview of AI technologies relevant to compliance.

  • Machine learning and deep learning in AML.
  • Natural language processing for document review.
  • Robotic process automation in workflows.

AI-powered transaction monitoring and anomaly detection.

  • Behavior pattern recognition.
  • Reducing false alerts.
  • Detecting emerging fraud schemes.

Enhancing Know Your Customer (KYC) with AI tools.

  • Biometric verification methods.
  • Real-time onboarding.
  • Continuous customer monitoring.
  • Group exercise: Design a Finance workflow tailored to a specific use case.

Automating due diligence and customer risk profiling.

  • Risk scoring models.
  • Automated watchlist checks.
  • Dynamic risk updates.

Using Natural Language Processing for regulatory document review.

  • Extracting critical obligations.
  • Identifying compliance gaps.
  • Automating regulatory change tracking.

AI applications in sanctions screening and PEP checks.

  • Fuzzy matching techniques.
  • Multilingual data screening.
  • Reducing false positives in screening.

Predictive analytics for compliance risk forecasting.

  • Trend analysis on fraud patterns.
  • Forecasting regulatory breaches.
  • Prioritizing high-risk entities.

Ethical considerations and data privacy in AI adoption.

  • Data protection regulations (GDPR, etc.).
  • Avoiding misuse of sensitive data.
  • Ensuring explainability in AI.

Case Study of AI compliance platforms.

  • Key features of leading platforms.
  • Success stories from implementation.
  • Lessons learned from failures.

Action plan for implementing AI in compliance operations.

  • Roadmap for adoption.
  • Training and capacity building.
  • Measuring success with KPIs
Register Now