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IAQF & Thalesians Seminar Series: Towards Professional Readiness of LLMs in Financial Regulations - A Seminar by Xiao-Yang Liu
6:00 PM Seminar Begins
7:30 PM Reception
Hybrid Event
Location:
Fordham University
McNally Amphitheater
140 West 62nd Street
New York, NY 10023
Free Registration!
For Virtual Attendees: Please email web@iaqf.org for the link.
Abstract:
In this talk, Xiao-Yang Liu will showcase their FinGPT--an open-source counterpart of BloombergGPT, on financial regulations. In particular, the team's two-year efforts on benchmarking financial large language models, with a zooming in Financial Regulations. He will also share ongoing projects in GenAI Research on Open Finance at Columbia University.
The financial industry operates within a labyrinth of complex regulations & industry standards designed to maintain market integrity & ensure reliability in financial reporting & compliance processes. Intricate financial regulations & standards have presented significant challenges for financial professionals & organizations. Large language models (LLMs), such as GPT-4o, Llama 3.1, & DeepSeek's V3/R1 models, have shown remarkable capabilities in natural language understanding & generation, making them promising for applications in the financial sector. However, current LLMs face challenges in the domain of financial regulations & industry standards. These challenges include grasping specialized regulatory language, maintaining up-to-date knowledge of evolving regulations & industry standards, & ensuring interpretability & ethical considerations in their responses.
Bio:
Dr. Xiao-Yang Liu graduated in Electrical Engineering of Columbia University. He is part-time researcher at Lab GenAI Research on Open Finance, Columbia University, & a faculty member in RPI's CS department. His research interests include Reinforcement Learning, Large Language Models, Quantum Computing, & applications to finance. He created the popular open-source projects, FinGPT, FinRL, & ElegantRL.
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