Axyon AIMar 25, 2025 10:40:30 AM8 min read

Roundtable - AI Trends in Investment Management

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AI Trends in Investment Management

London, 25 March 2025 - A recent roundtable organised by Axyon AI brought together voices from the financial sector to discuss whether AI is truly transforming investing or is the latest in a long line of overhyped technologies.

With representatives from traditional asset management, quantitative, and fintech investing, the 90-minute discussion navigated the complexities, promises, and challenges of AI in finance. In this article, we summarised the key topics raised by our panellists and guests during the roundtable discussion.

Roundtable - Featured Speakers

Carolina Minio Paluello - Speaker

Founder and CEO of Vitruvya. Quantitative and Fintech Business Leader, former CEO of Arabesque AI, former partner of Schroders, Lombard Odier IM and GSAM.

Gary Chropuvka - Speaker

Quantitative Business Leader, former President of WorldQuant and Co-Head of Quant Strategies of GSAM.

Yazid Sharaiha - Speaker

Global Head of Systematic Strategies at Norges Bank Investment Management.

Giovanni Beliossi - Moderator

Head of Investment Strategies at Axyon AI.

Key Topics of Discussion

📌 AI's Most Immediate Impacts: Efficiency & Performance

AI’s primary contribution lies in driving operational efficiency. It empowers non-coders and fundamental managers alike to analyse broader datasets quickly, improving workflow and insight without consistently outperforming markets.

AI can enhance speed and scope across financial services.
Non-technical users can now access advanced technologies, levelling the playing field.

📌 Explainability and Trust: Non-Negotiables in Finance

AI models must be transparent and interpretable to gain traction in finance. Regulatory demands and client expectations mean black-box systems won’t suffice; explainability tools are helping, but there’s still ground to cover.

Finance requires models that are auditable and justifiable.
Explainability fosters trust, especially critical to explain potential underperformance.
Axyon Lens provides a wide range of reports, from high-level strategy performance to a detailed examination of model predictions including: Strategy performance, risk & performance attribution, feature group importance & performance contribution, individual input features importance & performance contribution, pattern & interaction analysis and raw data; amongst many.

More about Explainability & Performance Attribution ✅ In this vein, firms like Axyon AI have invested significantly in building tools such as the Axyon Lens, which enables full ex-post performance attribution. This includes feature-level insights using SHAP values, signal strength assessment through Relative Information Contribution (RIC), and an understanding of the shifting importance of individual features and feature groups over time. Such depth not only supports transparency and accountability but also underscores how explainability is evolving from a regulatory checkbox into a core pillar of trust in AI-driven investment processes.

📌 Predictive AI vs Generative AI: Choosing the Right Tool for Investment Decision-Making

Generative AI excels at handling unstructured data and creating content, but when it comes to forecasting market behaviour, Predictive AI—built on Auto-ML frameworks—offers the precision, repeatability, and robustness essential for decision-making in noisy financial environments.

Generative AI is best suited for content creation, not alpha generation.
Predictive AI identifies subtle patterns to forecast asset performance.
Axyon AI offers a differentiated edge with finely tuned Predictive AI models that seamlessly integrate into investment processes across quantitative, fundamental, and wealth management domains.

More about Predictive AI & Generative AI

While generative AI often demands significant computational resources, the conversation highlighted that predictive AI, when applied effectively, can deliver meaningful insights with greater efficiency—especially as the availability of diverse data sets continues to grow. The ability to uncover and adapt to evolving market correlations hinges not only on access to high-performance computing but also on having a focused, specialised team. As noted during the discussion, success in AI-driven investment is less about the sheer size of the operation and more about the clarity of purpose and depth of expertise.

✅ Firms like Axyon AI, which have been dedicated exclusively to predictive AI since 2016 and maintain a live track record of strategies dating back to 2018, exemplify how scale can be redefined through precision and specialisation.

📌 The Human-Machine Collaboration Is Key

Successful adoption of AI hinges on collaboration between finance professionals and technical experts. The most effective results come when investment intuition is combined with AI capabilities, bridging the gap between traditional and quantitative approaches.

Domain knowledge and tech expertise must work hand-in-hand.
“Quantamental” investing reflects the new hybrid model powered by AI.
Isolated innovation efforts without integration fall short of value.

📌 AI vs. the Index
The panel explored whether an AI-enhanced index could outperform an equally AI-supported active manager. While passive investing sets a high benchmark through customisation and transparency, active strategies must now evolve with precision and adaptability to remain competitive and justify their cost.

Active managers must leverage AI to deliver targeted, dynamic exposure; with an aim of out-performing the benchmark.
Axyon AI combines Predictive AI with systematic rigour, offering proven, taylored strategies backed by live clients since 2018, which consistently outperform.

The Role of Predictive AI

✅ This evolving landscape is precisely where Axyon AI positions itself—with a proven approach that combines predictive AI with systematic rigour. While many asset managers are still navigating how to effectively integrate AI into their workflows, Axyon AI has been purpose-built for this challenge since inception.

Backed by a live track record dating to 2018, Axyon AI’s strategies have consistently demonstrated their ability to deliver differentiated outcomes. In fact, in 2024, if a client had equally allocated across all of Axyon AI’s publicly available strategies, they would have achieved a notable level of alpha outperformance versus the relevant benchmarks. This not only affirms the firm’s predictive capabilities but underscores the real-world value of AI-enhanced active management when implemented with clarity, focus, and precision.

📌 Rethinking Scale: Why Focus and Agility Matter More Than Size in AI-Driven Investing

The panel challenged the assumption that scale guarantees success in AI-driven investing. Instead, strategic clarity, agility, and effective use of accessible technologies were seen as more decisive than having the largest teams or most powerful infrastructure.

Effective deployment of AI depends more on focus than sheer size.
Democratised access to tools reduces the advantage of scale.
Success comes from adaptability and smart application—not just resources.

📌 Efficiency – From Silos to Synergy: How AI Is Merging Breadth and Depth in Investment Analysis
AI is collapsing the traditional divide between breadth and depth in investment research. Fundamental and quant managers alike are now leveraging AI to access richer insights across broader universes, redefining what it means to gain a sustainable information edge.

Fundamental managers can now scale analysis across vast stock universes using AI.
Quants are gaining depth through adaptive models capturing sentiment and behavioural data.
Predictive AI is driving a convergence of strategies, enhancing agility and insight.

Enhancing Investment Performance

✅ This is where firms like Axyon AI bring a differentiated edge. Our Predictive AI models are not only finely tuned to the complexities of the financial domain, but they are also built to integrate directly into front-office workflows—whether in quantitative, fundamental, or wealth management settings.

For fundamental teams, Axyon AI functions as an AI analyst, providing relative predictive performance rankings, weightings, and descriptors—potentially delivered through an AI Compass within a Portfolio Management System (PMS). For Quants, Axyon AI offers a new signal set to enhance strategy diversification and alpha potential.

Wealth managers can apply Axyon AI’s tools to gain a predictive lens into third-party mutual funds or ETFs, enabling better-informed product selection through look-through analysis. In the banking sector, predictive AI serves multiple use cases—from contributing differentiated signals to QIS strategies, to providing risk inputs for multi-day ADV trades in Central Risk Books (CRBs).

To further accelerate adoption, Axyon AI offers AI-Ready Factors—a derived dataset designed for seamless integration into clients’ own Auto-ML environments, enabling internal teams to evaluate, customise, and deploy predictive signals efficiently.

While generative AI holds enormous promise for communication and automation, predictive AI is where measurable investment outcomes are being realised today—a tool not of the future, but of the present, ready to enhance investment decision-making across the value chain.

📌 Where do We Go from Here? A Call for Purposeful Innovation

Collaboration with AI-focused fintechs offers a practical path forward. Rather than building in-house capabilities from scratch, firms can leverage partnerships—but only if both sides deeply understand the investment problems they aim to solve.

Partnerships enable scalable, specialised AI integration.
Understanding the business problem is key to successful AI use.
Axyon AI is a nimble, focused Predictive AI firm that delivers innovative, client-specific solutions with speed and precision through long-term partnerships, and robust financial market expertise.

Selecting the right AI & the best Technology Supplier

✅ Axyon AI is a nimble and highly focused predictive AI firm, known for its ability to innovate and deliver client-specific research and outcomes with speed and precision. Their approach is built around long-term partnerships, often spanning multiple years, which go beyond the provision of AI-powered insights to include meaningful knowledge transfer. For firms already investing in AI, Axyon offers a valuable opportunity to assess whether its outputs are orthogonal—and therefore complementary—to their own proprietary models. This is made possible by Axyon’s expert teams, which bring together deep research capabilities with strong expertise in investment and financial markets.

📌 Final Thoughts

AI is not replacing investment managers—but it is reshaping the role. Those who thoughtfully embrace AI as a tool for insight, efficiency, and collaboration will outperform those who resist. The future belongs to the adaptive.

AI changes how professionals think, work, and compete.
Success depends on thoughtful, collaborative adoption.
Investment managers using AI will outpace those who don’t.

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