Rethinking the Future of Finance: A Look Back at A High-Impact Workshop on AI and Finance

Hamid Boustanifar, EDHEC Associate Professor and Academic director of the MSc in Corporate Finance & Banking organised a cutting-edge workshop in Nice on May 27, 2025. It featured keynote-style presentations on a range of topics delivered by a mix of top academics and industry experts from leading institutions. Each speaker outlined the current state of their field, its applications in finance, and the way forward.

• To see the full programme, go to the dedicated webpage

Bringing together around 40 professors and PhDs from diverse disciplines (including finance, economics, accounting, mathematics, computer science, and physics), as well as professionals from industry, the workshop fostered deep dialogue across emerging intersections of finance, machine learning, big data, and sustainability.

Feedback was overwhelmingly positive. Participants praised the clarity, insight, and rigor of the discussions, while speakers emphasized the advantages of keynote-style talks for exploring connections between distinct yet related areas within AI.

Embracing Complexity: Machine Learning and the New Asset Pricing Paradigm

The workshop opened with a presentation by Professor Semyon Malamud (EPFL), who challenged a foundational principle in economics: the preference for parsimony. In his talk, "Deep Learning in Finance," Malamud argued—contrary to conventional wisdom—that complexity can be a virtue, and that increasing model complexity can improve predictions of stock returns.

His central finding: machine learning portfolios perform better when model parameterization exceeds the number of training observations—provided it is done thoughtfully. This insight challenges traditional econometric orthodoxy and reframes the debate around model specification. As Malamud noted, while economists often cite George Box and William of Occam in support of simplicity, such principles may lead to what he terms “Occam’s Blunder”—oversimplifying in a world where no model is ever truly “correct.”

The Journey Towards Smarter Financial AI: Past, Present & Future

In a dynamic and forward-looking keynote, Peter Hafez, Chief Data Scientist at RavenPack, offered a practitioner’s perspective on the evolution of artificial intelligence in financial markets. His talk, "The Journey Towards Smarter Financial AI," provided both a retrospective on the field and a strategic vision for the future.

Hafez began by outlining the profound ways in which financial workflows are being transformed—not by hype, but by advances in data infrastructure, AI tools, and intelligent systems. Drawing on over 15 years of experience in quantitative finance, he illustrated how technologies such as content retrieval systems, large language models (LLMs), and autonomous agents are changing how institutions process information and make decisions.

His core message was a call to shift focus from hype to application. While LLMs are undeniably powerful, their real value lies in how effectively they are integrated into specific financial use cases—from sentiment analysis to market surveillance and risk prediction.
Through real-world examples and lessons learned at RavenPack, Hafez emphasized the importance of pragmatism, scalability, and domain relevance when deploying AI in finance. His talk resonated strongly with students and practitioners seeking to understand how theory translates into practice in today’s fast-moving data environment.

AI and Quant Investing: Unlocking the Next Generation of Alpha

In his keynote, “AI and Quant Investing,” Dr. Mike Chen (Head of Next Gen Research at Robeco) explored how artificial intelligence, machine learning, and sustainability are reshaping the frontier of quantitative investing.

He made a compelling case for how this emerging toolkit can help uncover non-traditional signals and build adaptive investment frameworks. However, Chen also cautioned that integrating these new methodologies with existing frameworks brings both opportunities and challenges—from model interpretability to compatibility with risk systems and regulatory standards.

With a background spanning BlackRock, PanAgora, Google, and academia (MIT), Chen brought a rare perspective at the intersection of cutting-edge research and real-world portfolio management. His talk underscored that the future of quant investing depends not only on innovation, but also on strong governance, interdisciplinary thinking, and a commitment to long-term value creation.

Finance Meets Social Media: Understanding Markets Through a New Lens

In his keynote, “Finance in Social Media: The Future,” Professor Tony Cookson (Leeds School of Business, University of Colorado Boulder) examined one of today’s most dynamic frontiers: the intersection of social media, artificial intelligence, and financial decision-making.

Cookson reframed social media as more than just noise—it acts as a lens into economic behavior, revealing signals that reflect underlying social and financial dynamics. Drawing from his own empirical research, he highlighted how platforms like Twitter, Reddit, and Google Trends can offer powerful predictors of behaviors in areas such as housing, trading, and economic mobility.

A key theme was the dual role of AI in this space. On one hand, AI enables the detection of previously unmeasurable constructs, uncovering subtle patterns in public sentiment and market behavior. On the other, the rise of AI-generated content raises questions: Does AI democratize access to valuable insights, or obscure them behind new layers of complexity?
Cookson’s work shows that social media content often exhibits internal consistency and predictive power. His research illustrates, for example, how textual analysis of user-generated content can inform investment strategies, and how online behavior reflects regional or asset-specific trends.

The session encouraged participants to think critically about how AI and social media are not just transforming communication, but also reshaping the informational fabric of modern markets.

Networks and Finance: A Tale of Connections

In a thought-provoking keynote titled “Networks and Finance: A Tale of Connections,” Professor Renaud Lambiotte (University of Oxford) introduced participants to the powerful tools of network science for understanding financial systems.

Lambiotte, an expert in modeling complex networks, emphasized that finance is fundamentally about connections—between institutions, assets, agents, and flows of information. Using tools from network theory, he illustrated how we can better analyze contagion, clustering, systemic risk, and influence propagation.

Drawing on examples from both finance and social systems, he showed how temporal networks, community detection, and nonlinear dynamics can yield deep insights into interconnected behavior. He also discussed how networks help uncover the hidden geometry of financial interactions, offering a systems-level understanding that goes beyond linear models.

The talk bridged theoretical physics and modern finance, leaving the audience with a strong sense of how network thinking can reveal vulnerabilities, resilience patterns, and emergent dynamics in today’s complex financial world.

Bridging Finance, Climate Science, and Language: A Journey Towards Actionable Insights

In his keynote, Professor Markus Leippold (University of Zurich and Google DeepMind) presented a compelling vision for integrating finance, climate science, and natural language processing (NLP) to generate actionable insights in the era of sustainable investing.

Leippold’s research focuses on analyzing corporate climate communication—from sustainability reports to earnings calls—using advanced AI models. His findings highlight the opacity and inconsistency in much of today’s climate discourse, complicating efforts to assess true corporate progress.

Using machine learning, Leippold and collaborators identify patterns of climate lobbying, detect greenwashing, and assess transparency. He emphasized that language is more than a communication medium—it’s a rich data source. Properly analyzed, it reveals discrepancies between what firms say and what they do—crucial insights for both policy and investment.
He also introduced Frigg, a platform he co-founded to connect climate-conscious investors with verified sustainable projects, showcasing how academic research can drive practical innovation at the intersection of technology and green finance.

Crypto, Blockchain, and the Future of Finance

Professor Marco Di Maggio (Imperial College London) concluded the event with a keynote on crypto, blockchain, and fintech disruption, expanding on work previously conducted at Harvard Business School.

He provided detailed insights into the characteristics of investors in these markets and explored future developments that could revolutionize finance and adjacent sectors.

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A Resounding Impact: Reflections and Momentum for the Future

The workshop not only showcased world-class expertise at the intersection of finance, AI, and data science, but also sparked deep intellectual engagement across academic and professional communities.

From transformer models in portfolio optimization to strategic uses of LLMs in finance, the discussions offered actionable insights already shaping projects at major financial institutions. The quality and depth of exchange were widely praised, and many attendees expressed strong interest in continued collaboration and future editions.

All in all, the success of this edition confirms the value of the initiative and sets a strong precedent for its continuation in the years ahead. As one participant noted: “The workshop has given us much to reflect on and has personally motivated me to delve deeper into AI applications in finance.”