This half-day tutorial is designed to explore the significant impact of Agent AI in the financial sector.
Highlighted by the advancements in large multi-modal language models, this session aims to provide attendees with an in-depth understanding of the latest methodologies, concepts, and frameworks necessary for creating, deploying, and assessing AI agents. These agents are equipped for multi-modal comprehension, decision-making, and interaction, with a special emphasis on human-centric decision-making and multi-agent cooperation in finance. The tutorial will navigate through the current landscape of financial applications of AI, setting the stage for future research and development directions.
Targeting an audience that spans from first-year PhD students to experienced researchers in AI and finance, the tutorial will offer an overview of the recent trends in Agent AI for finance. Participants will be introduced to foundational concepts, enabling them to understand the field and carve out their research paths, while also encouraging experienced researchers to partake in discussions on open research questions, enriched by pilot experimental results. The session is designed to foster a collaborative learning environment, enhancing research directions and benefiting attendees across various experience levels. With financial data’s transparency and availability serving as a backdrop, the tutorial will explore a range of tasks such as decision-making, multimodal data understanding, sentiment analysis, fraud detection, and more, through a lens that emphasizes the importance of AI agents in investor education, consumer protection, and market commentary generation.
