SFI Master Classes

Currently fully booked;
registrations possible on the waiting list.

This SFI Master Class is offered in cooperation with the Zürcher Bankenverband (ZBV).

Current Situation

Recent advances in artificial intelligence have moved beyond systems that merely answer questions toward systems that can take goal-directed actions, interact with tools, and iteratively refine their outputs. These so-called agentic AI systems are increasingly used to automate research workflows, monitor risks, synthesize large volumes of information, and support decision-making across the financial industry.

In finance, this shift is particularly consequential. Analysts, portfolio managers, and risk teams routinely work with unstructured data such as corporate disclosures, regulatory filings, and reports. Agentic AI systems can now assist with these tasks by autonomously retrieving relevant information, structuring analyses, and producing preliminary reports. At the same time, these systems introduce new challenges related to robustness, oversight, feedback loops, and governance.

As financial institutions explore the adoption of such technologies, a clear conceptual understanding—and a realistic assessment of both opportunities and limitations—has become essential.
 

Objective

Building on recent developments in artificial intelligence and practical finance applications, this Master Class provides a high-level, intuitive introduction to agentic AI systems, with a particular focus on their relevance for financial research and analysis.

The Master Class combines conceptual explanations and concrete Use Case examples with hands-on Jupyter Notebook exercises, allowing participants to directly experiment with simplified agentic workflows using public financial data. The objective is not to promote automation for its own sake, but to equip participants with a clear mental model of what agentic AI can—and cannot—do in a finance setting.

The specific objectives are:

• Understanding what distinguishes agentic AI systems (goal-directed, tool-using, persistent) from traditional reactive language models.

• Learning the core building blocks of an AI agent: goals, planning, tool use, memory, and feedback.

• Exploring concrete financial use cases, such as automated analysis of corporate disclosures (e.g. 10-K filings), risk factor extraction, and peer comparisons.

• Providing Guidance to Finance Leaders on how to leverage Agentic AI.

• Discussing Agentic AI Governance and the risks associated with autonomous systems, including misaligned objectives, fragile feedback loops, and the need for human oversight.

• Exploring the impact of Agentic AI on processes, culture and organization. 

• Developing an informed perspective on how agentic AI could responsibly augment financial workflows rather than replace human judgment.
   

SFI Master Class Features and Target Audience

SFI Master Classes offer seasoned banking and finance professionals a unique opportunity to exchange knowledge and perspectives with leading academics and practitioners in an interactive learning environment. The format emphasizes discussion, conceptual clarity, and hands-on experimentation rather than technical depth.

This Master Class includes live demonstrations and executable Jupyter Notebooks illustrating simplified agentic AI workflows applied to financial data. The notebooks are intentionally illustrative and transparent, highlighting core ideas rather than production-scale implementations.

The Master Class is aimed at banking and finance professionals and leaders who are not AI specialists but who wish to better understand how recent AI developments may affect their workflows and processes incl. research, investment analysis, and risk management. This includes professionals working in asset management, private banking, research, risk, senior management, and strategy functions who seek a structured and realistic introduction to agentic AI in finance.

An on-site networking event will follow the Master Class.

SAQ Recertification

This SFI Master Class is an acknowledged SAQ recertification measure and comprises four learning hours for the following SAQ profiles: 

• Wealth Management Advisor CWMA
• Advisor Affluent Clients
• Advisor Individual Clients
• Advisor Private Clients
• Certified Corporate Banker CCoB
• Advisor SME Clients

This SFI Master Class covers the aspect "industry knowledge" and "conduct."
 

Late cancellations and no-shows

If you have registered for a Master Class but are unable to attend, we kindly ask that you inform us as soon as possible. Places are limited, and late cancellations and no-shows not only prevent those on the waiting list from attending, but also result in an inefficient allocation of valuable resources. Your cooperation in communicating any unexpected changes regarding your participation at this Master Class is greatly appreciated.