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Course Outline
Foundations of Generative AI
- Understanding generative models and their strategic value in finance
- Key architectures: LLMs, GANs, and VAEs
- Analyzing strengths and constraints within financial environments
Leveraging GANs for Financial Applications
- Explaining GAN mechanics: the interplay between generators and discriminators
- Utilizing GANs for synthetic data creation and fraud scenario simulation
- Practical application: creating realistic transaction datasets for testing purposes
LLMs and Advanced Prompt Engineering
- How LLMs process and generate financial documentation
- Crafting effective prompts for forecasting and risk assessment
- Real-world applications: summarizing reports, KYC verification, and identifying red flags
Enhancing Financial Forecasts with Generative AI
- Time-series forecasting using hybrid LLM and ML approaches
- Generating scenarios and conducting stress tests
- Case study: predicting revenue by combining structured and unstructured data
Advanced Fraud Detection and Anomaly Recognition
- Deploying GANs to detect anomalies in transactional data
- Recognizing emerging fraud patterns via LLM-driven workflows
- Model assessment: distinguishing false positives from genuine risk indicators
Regulatory and Ethical Considerations
- Ensuring explainability and transparency in AI outputs
- Mitigating risks associated with model hallucinations and bias
- Aligning with regulatory standards such as GDPR and Basel guidelines
Developing Generative AI Strategies for Financial Institutions
- Constructing compelling business cases for internal adoption
- Balancing innovation with risk management and compliance needs
- Establishing governance frameworks for responsible AI deployment
Conclusions and Future Directions
Requirements
- A solid grasp of fundamental finance and risk management principles
- Proficiency with spreadsheets or introductory data analysis
- Knowledge of Python is advantageous though not mandatory
Target Audience
- Risk managers
- Compliance analysts
- Financial auditors
14 Hours
Testimonials (1)
i already have some reports that i know, i will use some of the prompts that looked at today
