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Artificial Intelligence

Demystifying AI for Asset Managers

In the world of asset management today, the competition actively scouring markets for investment opportunities is smarter, more aggressive and more numerous than ever before.

Beating the benchmark often means putting in long hours and requires deep due diligence and information gathering. Just as important, however, is a keen understanding of how emerging technologies like artificial intelligence (AI) and machine learning (ML) may be able to support this work and be integrated into wealth and asset management.

Innovation in these areas has captured the attention of asset managers on the lookout for that extra edge, although questions linger over how best to effectively incorporate this technology, especially given ethical and regulatory considerations.

Generative versus Predictive AI

Firstly, there’s an essential distinction between these two AI versions being developed today. While both types of AI have been used to enhance investment strategies for decades, their applications and implications differ significantly.

Based on user input, Generative AI, which underpins large language models (LLMs) such as OpenAI’s ChatGPT, focuses on creating new content by learning from existing data patterns and translating this data into different formats, such as text, image or other media. This form of AI excels in generating creative responses. Its implementation in the financial services environment can help asset managers in portfolio construction by assisting them to create diversified investment strategies and simulate thousands of market scenarios.

On the other hand, Predictive AI specialises in forecasting future events or trends based on historical data based on AI / ML models (in the financial scenario, we're talking about financial time series). It excels in pattern recognition, making it invaluable for predicting market movements and stock performance. As a result, it gives investment managers valuable insights to improve their investment strategies and risk management.

Understanding these distinctions is crucial for asset managers seeking to implement AI-driven strategies effectively, ensuring that they can harness the full potential of these technologies to boost investment performance.

Building better investment strategies and improving the client experience

As those two types of AI solutions can help managers drive superior investment outcomes, AI can also transform the experience through personalised interactions on the client front. The combination of AI-powered chatbots and virtual assistants provide immediate, tailored responses to client queries, making information access seamless and sophisticated. They also offer proactive insights and notifications about market developments and portfolio adjustments, keeping clients informed and engaged. Ultimately, the heightened level of personalisation and responsiveness bolstered client trust and deepened their understanding of their investment journey.

Making better decisions

As the potential of AI becomes more obvious and new products saturate the financial services sector, what factors should guide asset management firms who are searching for a WealthTech solution and are keen to get it right the first time?

Selecting an AI technology solution provider is critical for companies aspiring to leverage advanced AI technologies in their investment process. It's a strategic choice that demands careful consideration of various factors to ensure alignment with the client organisation's objectives and internal capabilities.

From gaining deeper insights into the company background and experience, from delving into their clients relationships and proven results, a successful procurement process must also consider learning how well the provider solutions fit the needs of the investment strategy and how they work differently to achieve results. This usually involves meeting experts and mutual exchange to understand what benefits managers can expect from integrating a new process. The value offered by each solution can be matched against a firm’s investment needs assessment, which identifies areas where AI is likely to bring significant improvements, such as in cost control, the investment strategy performance or the client experience.

AI opportunities for investment managers

AI is not supposed to replace the judgement and intuition of someone with a strong knowledge of business ethics and decades of irreplicable experience in the field. It’s about how we combine this technology to get the most out of it and ensure it is used fairly and safely in the future.

AI and auto-ML hold tremendous promise for asset managers with a broad range of investment objectives. Professional investors embracing its increasing capabilities with open arms and considering AI-driven strategies will likely be rewarded with that extra edge in performance into 2024.


Giacomo Barigazzi is Co-Founder at Axyon AI


The views expressed in this article are those of the author and do not necessarily reflect the views of AlphaWeek or its publisher, The Sortino Group

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