Gen AI for Financial Risk Management for Enhanced Modeling

Gen AI for Financial Risk Management for Enhanced Modeling

Course Structure:

Introduction

• Lecture: Intro to the Course – An overview of the course structure, goals, and objectives in leveraging Gen AI for financial risk management.
• Lecture: Introduction to Gen AI – A deep dive into how advanced artificial intelligence is transforming financial risk assessment and decision-making processes.

Large Language Models (LLMs)

• Lecture: Introduction to LLMs – A comprehensive introduction to LLMs, discussing their capabilities in handling complex financial data and natural language processing tasks.
• Lecture: Public LLMs Overview – A detailed examination of popular public LLMs such as BERT, GPT, and RoBERTa, and their real-world applications in finance.
• Lecture: Using GPT and BERT in Finance – Practical use cases for sentiment analysis, financial forecasting, and risk evaluation using state-of-the-art language models.
• Lecture: ChatGPT and Gemini in Finance – Exploring the real-time capabilities of these models to generate insights and support decision-making in financial markets.
• Lecture: Model Differences – A comparative analysis of various LLMs focusing on performance, accuracy, and adaptability to financial use cases.
• Lecture: BERT’s Role in Finance – In-depth exploration of BERT’s applications in document classification, regulatory compliance, and financial reporting.

Synthetic Data Techniques

• Lecture: Generative Models – Understanding how VAEs and GANs create realistic synthetic financial data for model training.
• Lecture: VAEs in Financial Applications – Utilizing VAEs for anomaly detection and predictive analytics in financial institutions.
• Lecture: GANs for Fraud Detection – Harnessing GANs to generate synthetic data that enhances fraud detection and risk management capabilities.

Tools and Libraries for AI Development

• Lecture: Hugging Face Overview – A detailed guide on how Hugging Face’s ecosystem supports financial risk management through model deployment and fine-tuning.
• Lecture: Advanced Hugging Face Applications – Exploring real-time deployment of Hugging Face models to enable continuous monitoring and evaluation of financial risks.

Final Insights

• Lecture: Final Words – Summarizing the key concepts, best practices, and future trends in Gen AI for financial risk management.