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Course Outline
Introduction to Generative AI
- Overview of generative models and their relevance to finance
- Types of generative models: LLMs, GANs, VAEs
- Strengths and limitations in financial contexts
Generative Adversarial Networks (GANs) for Finance
- How GANs work: generators vs discriminators
- Applications in synthetic data generation and fraud simulation
- Case study: generating realistic transaction data for testing
Large Language Models (LLMs) and Prompt Engineering
- How LLMs understand and generate financial text
- Designing prompts for forecasting and risk analysis
- Use cases: financial report summarization, KYC, red flag detection
Financial Forecasting with Generative AI
- Time series forecasting with hybrid LLM and ML models
- Scenario generation and stress testing
- Use case: revenue prediction using structured and unstructured data
Fraud Detection and Anomaly Identification
- Using GANs for anomaly detection in transactions
- Identifying emerging fraud patterns through prompt-based LLM workflows
- Model evaluation: false positives vs true risk indicators
Regulatory and Ethical Implications
- Explainability and transparency in generative AI outputs
- Risk of model hallucination and bias in finance
- Compliance with regulatory expectations (e.g. GDPR, Basel guidelines)
Designing Generative AI Use Cases for Financial Institutions
- Building business cases for internal adoption
- Balancing innovation with risk and compliance
- Governance frameworks for responsible AI deployment
Summary and Next Steps
Requirements
- An understanding of basic finance and risk management concepts
- Experience with spreadsheets or basic data analysis
- Familiarity with Python is helpful but not required
Audience
- Risk managers
- Compliance analysts
- Financial auditors
14 Hours
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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Testimonials (3)
The background / theory of LLMs, the exercise
Joanne Wong - IPG HK Limited
Course - Applied AI for Financial Statement Analysis & Reporting
it has opened my mind to new tool that can help me in creating automation
Alessandra Parpajola - Advanced Bionics AG
Course - Machine Learning & AI for Finance Professionals
I very much appreciated the way the trainer presented everything. I understood everything even if Finance is not my area, he made sure that every participant was on the same page, while keeping up with the time left. The exercises were placed at good intervals. Communication with the participants was always there. The material was perfect, not too much, not too little. He elaborated very well on a bit more complicated subjects so that it can be understood by everyone.
