How might artificial intelligence shape the future of financial services? And what will be its impact on investors? Tackling these and other questions, some of the world's best mathematicians and theoretical scientists came together at Breaking Boundaries: The Adventure of Artificial Intelligence, an annual IHES (Institut des Hautes Études Scientifiques) symposium, to discuss and exchange ideas on the challenges ahead, which took place in New York City in November. BNP Paribas was the exclusive premier sponsor.
What does AI mean for banking? Why will it impact everyday investors? Some of the world's best minds came together at an event sponsored by BNP Paribas.
Clients, partners and internal specialists also led panel discussions at AI Discovery, a break-out following the IHES symposium and hosted by Jean-Yves Fillion, CEO of BNP Paribas USA and Head of Corporate and Institutional Banking (CIB) Americas. Our contributors included Mark Howard, Senior Multi-Asset Specialist at Global Markets Americas, and Edouard d'Archimbaud, Head of Data & AI, BNP Paribas CIB.
Specialists from technology companies such as Google, IBM Watson Lab, Kensho and Thasos joined representatives from leading institutional investors in discussions ranging from AI as "a new class of optimisation" and the reliance on AI for the collection of information (such as alternative data), to whether humans and machines are complementary for portfolio construction. The interactive programme featured two panel discussions: first, on how AI will transform the use of alternative data; and second, whether AI will augment the human investment process for superior returns.
"Some of the world's best mathematicians and theoretical scientists came together at Breaking Boundaries in New York City, with BNP Paribas as exclusive premier sponsor."
The first panel, focusing on alternative data, saw senior asset managers discussing why they were using these data sources to help generate alpha and better manage risks. In addition, independent research vendors explained how their products help customers tackle questions previously unaddressed until the explosion in alternative data sources. For example, how does mobile phone location data deliver insights on retail foot traffic? And how do loading dock deliveries relate to hours worked on assembly lines?
The second panel looked at how savvy investors, armed with mathematical models embedded in AI and driven by computing power increases, combined with the proliferation of data, were seeking to increasingly differentiate their returns. Panellists debated how AI may offer particular insights to investors in less liquid securities over time.