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Fit for Artificial Intelligence in Finance
University of St. Gallen

Fit for Artificial Intelligence in Finance

University of St. Gallen, St. Gallen
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Interested in this program?

No upcoming dates are listed right now. Register your interest and University of St. Gallen will let you know when the next cohort opens.

About This Program

This course provides a comprehensive introduction to deep learning and generative Artificial Intelligence (AI), with a particular emphasis on their applications in the financial industry. Participants will explore how these technologies are currently being used in areas such as retail banking, derivatives hedging, asset management, and algorithmic trading. The course not only covers the foundational principles of deep learning but also places a strong emphasis on practical implementation and current industry trends, discussed in collaboration with leading experts. It is designed for individuals seeking a thorough understanding of AI's impact on finance. No prior experience with AI is required, and participants will gain the knowledge needed to assess the potential and opportunities of AI in the financial sector.

Why University of St. Gallen?

HSG's executive programs are built around a single architectural idea: context-integrated learning, where economics, law, social sciences, and management are taught as a unified system rather than separate disciplines. That interdisciplinary structure, embedded in the school since its founding, produces graduates who reason across functions in a way that single-discipline business schools rarely match. For senior professionals who need to think across organizational silos, that is a concrete structural advantage.

Your Profile

  • Professionals in finance, banking, legal and management consulting, pension funds, and related fields who wish to deepen their understanding of artificial intelligence in the financial sector while staying up to date with current market trends.
  • Individuals working at the intersection of industry and finance, including asset management, banking, financial advisory, pension funds, risk management, insurance and finance IT, and corporate treasury.
  • No prior experience with AI or specific technical prerequisites required.

Benefits

  • Gain a structured, in-depth introduction to AI and deep learning without needing prior technical expertise.
  • Network with peers and industry experts in a dynamic and interactive environment across five thematic sessions.
  • Learn directly from top academics and professionals from organizations like UBS, EY, Nvidia, and the University of St.Gallen.
  • Stay ahead of the curve by exploring how generative AI and deep learning are transforming financial services.

What You'll Learn

  • Day 1: AI Overview - Overview on AI, machine learning and deep learning covering cross-industry applications, hardware and technical aspects; Generative AI: definition and overview on current main application areas within financial services, challenges and trends.
  • Day 2: Deep Learning in Finance - Overview on main application fields of deep learning and generative AI including forecasting, deep learning for trading, derivatives pricing and hedging, asset management; working principles underlying deep learning, optimization algorithms, computational graph structure.
  • Day 3: AI in Retail Banking & Hardware - Practical GenAI use cases for the financial services industry; deep learning in finance from a hardware industry perspective.
  • Day 4: AI in Asset Management and Trading - Large language models in asset management; case studies: deep asset-liability-management; reinforcement learning for optimal decision making in asset-liability-management.
  • Day 5: AI in Finance Outlook - Generative AI for trading; panel discussion on AI in finance outlook.

How to Apply

  1. 1

    Check your eligibility

    Review the entry requirements listed on this page. Most executive programs require 8–15 years of professional experience.

  2. 2

    Compare programs

    Use Gradia's comparison tool to evaluate up to 3 programs side-by-side on fees, duration, format, and accreditation.

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  3. 3

    Contact the school

    Send a message directly to University of St. Gallen via Gradia to request a brochure or speak with an admissions advisor.

  4. 4

    Prepare your application

    Gather your CV, reference letters, and any required test scores. Many EMBA programs waive standardised tests for senior candidates.

  5. 5

    Submit your application

    Apply directly through University of St. Gallen's official application portal.