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AI and ML applications in finance: opportunities, challenges and policy implications

AI and ML applications in finance: opportunities, challenges and policy implications

Day 1 Afternoon

Wednesday 26 April

Room :

ROOM 1

Speakers

Chair
Petra Hielkema
Chairperson - European Insurance and Occupational Pensions Authority
Public Authorities
Alex Ivančo
Director, Financial Markets III - Ministry of Finance, Czech Republic
Tsvetelina Penkova
MEP - Committee on Industry, Research and Energy, European Parliament
Caroline D. Pham
Commissioner - U.S. Commodity Futures Trading Commission
Nikhil Rathi
Chief Executive Officer - Financial Conduct Authority
Industry Representatives
Ash Booth
Head of Artificial Intelligence - HSBC Holdings plc
Georgina Bulkeley
Director, Financial Services Solutions - Google Cloud
Diana Paredes
Chief Executive Officer & Co-Founder - Suade Labs

Objectives

This session will discuss the uptake of artificial intelligence and machine learning (AI and ML) use in the financial sector, how it is expected to evolve in the coming years, potential benefits and challenges of a wider use of AI in the financial sector and the implications of other technologies such as cloud services and high performance computing for the development of AI.
The panel will also assess the policy implications of a wider development of AI and ML in finance, whether these are appropriately taken into account in the EU AI and data frameworks that are in the process of being adopted (AI Act, EU data framework), whether any further measures are needed to support an appropriate development of AI in the financial sector and how the EU approach in this area compares with those in other jurisdictions (US, UK).

Points of discussion

  1. How is the use of AI and ML progressing in the financial sector and is it reaching a tipping point? What are the main use cases of AI and ML and are they expected to fundamentally evolve in the coming years with new generations of AI such as generative AI? What are the main opportunities and challenges related to AI and ML use in the financial sector? What are the main drivers of AI adoption and are reasons for implementing AI systems in the financial sector expected to evolve?
  2. Do the AI Act and the European strategy for data provide an appropriate framework for supporting the uptake of AI in finance? How do EU AI and data rules compare with approaches at the international level and in other jurisdictions? Are further efforts needed in terms of data quality and standardization to support AI uptake?