AI for Fraud Detection & Anti‑Money Laundering Training Course
Artificial intelligence is revolutionizing the way financial institutions identify fraud and combat money laundering by leveraging intelligent, real-time analysis of large-scale transaction data.
This instructor-led, live training session, available online or onsite, targets intermediate-level professionals seeking to utilize machine learning and AI tools to automate and strengthen financial crime detection, compliance monitoring, and operational governance.
Upon completing this training, participants will be equipped to:
- Grasp key AI use cases within fraud detection and AML monitoring contexts.
- Design and deploy models for anomaly detection and transaction scoring.
- Apply graph-based AI techniques to detect network risks.
- Ensure that model deployment adheres to ethical standards, provides explainability, and meets regulatory requirements.
Course Format
- Engaging lectures paired with interactive discussions.
- Extensive exercises and practical applications.
- Hands-on implementation within a live laboratory environment.
Course Customization Options
- To arrange a customized training session for this course, please get in touch with us.
Course Outline
Introduction to AI in Financial Crime
- Overview of fraud and AML in the digital finance era
- Traditional vs AI-based approaches
- Case studies from Mastercard, JPMorgan, and global banks
Machine Learning for Transaction Monitoring
- Supervised learning for risk scoring and classification
- Unsupervised learning for anomaly detection
- Real-time alert generation and stream processing
Graph Analytics and Network Risk Detection
- Modeling relationships between entities and transactions
- Detecting complex fraud schemes using graph AI
- Hands-on with Neo4j or similar tools
Natural Language Processing for AML
- Text mining in customer due diligence (CDD)
- Watchlist scanning using named entity recognition (NER)
- Prompt-based document review and suspicious activity reports (SARs)
Model Governance and Explainability
- Building explainable and auditable models
- Bias detection and mitigation in fraud detection algorithms
- Use of XAI techniques in compliance settings
Ethics, Regulation, and Model Risk
- Compliance with AML and KYC frameworks (e.g. FATF, FinCEN, EBA)
- AI ethics in surveillance and customer monitoring
- Reporting standards and regulatory auditability
Deployment Strategies and Future Trends
- Integrating AI models into existing transaction systems
- Feedback loops and model updating mechanisms
- Future of generative AI in fraud investigation and SAR automation
Summary and Next Steps
Requirements
- Knowledge of fraud risk and AML procedures
- Experience in data analysis or compliance reporting
- Basic familiarity with Python or analytics platforms
Audience
- Fraud risk professionals
- AML compliance teams
- Security managers
Open Training Courses require 5+ participants.
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NobleProg offers professional training programs designed specifically for companies and organizations. These trainings are not intended for individuals.
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Testimonials (1)
Trainer was very knowledgeable and easy to speak to
Gareth Gird - Teleflex Medical Europe Ltd
Course - Copilot for Finance and Accounting Professionals
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