Large Language Models in Finance

Participants of this course will:

• Understand key concepts of Natural Language Processing (NLP) and its applications in finance
• Gain foundational knowledge of large language models, including the Transformer architecture and tools like Hugging Face Transformers for financial applications
• Develop an understanding of data preparation, training, and fine-tuning techniques for large language models
• Explore transfer learning and how pre-trained language models can be customized for specific financial tasks like forecasting and sentiment analysis
• Learn how to leverage large language models for business valuation tasks, including forecasting cashflows and conducting scenario analysis
• Gain hands-on experience with entity recognition from financial statements and how LLMs can be used for comparable selection in valuations
• Master the techniques of fine-tuning large language models for credit risk assessment and estimating probabilities of default
• Learn how to deploy LLM applications using a REST API to handle real-world financial decision-making under uncertainty
• Explore advanced applications of LLMs in finance, including forecasting returns, fraud detection, and dynamic web scraping of financial data
• Understand the ethical considerations and biases in financial models, and how to mitigate them for responsible AI use in finance