Description
The Certificate Program on Anti-Money Laundering (AML) with AI is a specialized training program designed to educate professionals on the risks, legal frameworks, and best practices for preventing and detecting money laundering activities. This program integrates Artificial Intelligence (AI) in AML processes, offering insights into how AI-driven analytics, machine learning models, and automated monitoring systems enhance compliance and risk management.
Participants will gain hands-on knowledge of AI-powered transaction monitoring, predictive risk assessment, and anomaly detection techniques, strengthening their ability to combat financial crime efficiently.
What Will I Learn
You will be able to:
- Understand global AML regulations and the role of regulatory bodies.
- Assess and mitigate AML risks using AI-based risk analytics.
- Identify and report suspicious transactions using machine learning-based fraud detection.
- Learn case studies on AI-driven AML compliance in banking and financial sectors.
- Utilize AI tools for enhanced transaction monitoring and pattern recognition in money laundering activities.
Curriculum
- ML/ TF Concepts & Risks
- Global Framework & Guidelines
- FATF Standards 2012 (June 2019)
- National Framework
- PMLA: ML Offence
- PMLA: RE’s Obligations
- PMLR Norms
- Organizational Framework
- KYC-AML Policy
- Customer Identification
- Beneficial Owners
- Customer Due Diligence
- Special Cases of Customers
- Risk Based Approach
- Case: PMC Bank
- FIU Reports: Overview
- CTR/ CBTR/ NTR
- Money Laundering Modalities
- Case: Saradha Group
- Suspicion Transaction Scope
- Monitoring Transactions
- Red Flag Indicators
- Case: PMC Bank
- STR Modalities
- Case: IL&FS
- Shell Companies
- Case: DHFL – Yes Bank
- Cross Border Transactions: Overview
- Case: Panama Papers
- CBT Norms
- Case: Nirav Modi
- Dark World
- Countries Risk
- Trade Based Money Laundering
- Case: Import Remittances
- Terrorist Financing
- Records Maintenance
- Introduction to Artificial Intelligence (AI)
- Role of AI & Machine Learning in AML
- Machine Learning for Transaction Pattern Recognition
- AI-Based Customer Due Diligence (CDD) Enhancements
- Case Study: AI in AML for Global Banks
- Generative AI in Risk Management
- NLP for Analysing Suspicious Communication
- Predictive Analytics in AML Investigations
- Case Study: AI-driven Suspicious Activity Reporting (SAR)
How It works
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Live Online Sessions Each session is interactive and informative, featuring case studies, quizzes, and projects |
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Interact, Learn and Grow bsevarsity.com enables you to master the concepts, interact with expert faculty and other learners, and be a part of the community whilst growing. |
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