Gen AI for the financial sector

Unternehmensinterne Weiterbildung

An wen richtet sich die Weiterbildung?

Employees, from all levels, of the financial sector (AWM, alternatives, insurance, banks, asset service providers).

Erreichtes Niveau

Anfänger

Dauer

4,00 Stunde(n)

Sprache(n) der Dienstleistung

EN FR

Ziele

By the end of this training, participants will be able to:

  • understand the foundational principles of Generative AI, including its opportunities and limitations within the financial sector;
  • explore practical use cases relevant to their industry;
  • gain hands-on experience with tools like CoPilot and ChatGPT for prompt engineering;
  • familiarise themselves with regulatory impacts, including the EU AI Act and other pertinent regulations;
  • acquire insights into governance and security best practices essential for managing AI implementations responsibly;
  • get information about upcoming developments and updates shaping the future of AI in finance.

Inhalt

  • Introduction to GenAI
  • Gen AI: opportunities and limitations
  • Examples of use cases in the industry
  • Demo life with CoPilot/ChatGPT
  • Prompt engineering (participants are free to bring their own lapop to practice)
  • Regulatory impact: EU AI Act and other regulations
  • Governance and security
  • The way ahead: what are the next developments / update?

Zertifikat, Diplom

An attendance certificate will be sent to the participants.

Zusätzliche Informationen

This training is coordinated by Sébastien Schmitt, Partner at PwC Luxembourg and Mustafa Aldemir, Director at PwC Luxembourg.

Sébastien Schmitt, Partner at PwC Luxembourg, assists asset managers with risk and regulatory requirements. He has spent 13 years in consulting for Big 4 firms and assisting asset managers but also bankers and insurers with risk, transparency and regulatory requirements. Sébastien has developed strong experience in risk management, financial and alternative investments.

Mustafa is an accomplished Artificial Intelligence director with a successful track record managing Machine Learning and GenAI projects for major clients. His diverse skill set encompasses Machine Learning, Deep Learning, MLOps, cloud architecting and software development. He is well-versed in cloud technologies, including AWS, Azure and GCP. He has been participating in global events to share insights on ML and AI. Thanks to his doctoral research in Deep Learning, he is able to combine theoretical knowledge with practical expertise.

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