AI in Investment Management – Navigating Regulatory Scepticism Towards Future Value

It’s hard to miss the growing coverage and interest in the topic of artificial intelligence (AI) and, in particular, how it has moved into the public and mainstream consciousness through the intense attention on ChatGPT (see Alpha’s last article Blueprint for Success: Demystifying ChatGPT for Asset Managers – Alpha FMC detailing use cases and risks associated with generative AI). Attention has also increased as a result of global technology brands such as Microsoft or Google launching new and exciting AI products such as Azure AI, Bard, and PaLM 2.

In the past six months, major regulators such as ESMA, SEC, and the Bank of England have published materials highlighting the potential use cases and outlining the risks and concerns over AI usage. One of the examples across published papers is the ESMA report ‘Artificial intelligence in EU securities markets’ which provides insight into the regulatory perspective and industry professionals’ view on AI. ESMA’s report published in February 2023 presents a sceptical view of the potential that AI technologies can bring. The report states that AI hasn’t led to a disruptive transformation in investment processes, highlighting that only very few funds refer to the use of AI/Machine Learning (ML)  in their investment processes.

Similarly, the industry professionals interviewed for the report comment that “it does not seem to be leading to a fast and disruptive overhaul of business processes.” The report also covers a number of regulatory concerns focusing on effective governance and human oversight. Similarly, Alpha’s observations and preliminary analysis reveal an incremental number of use cases where AI technology can effectively enhance existing processes without necessarily causing a disruptive change. Moreover, early adopters are likely to get accustomed to this novel technology and be in a stronger position to harness the exponential gains as the technology becomes more prominent in the industry.

We conducted a term search analysis on the annual reports of the 10 largest global asset managers by AuM and saw the mention of AI-related technology concepts such as ‘natural language processing’ or ‘robo-adviser’ grow by 197% since 2016 and 98% since 2021. In parallel, Google searches for the term ‘AI in Asset Management’ rose by 547% between 2016 – 2022 – highlighting that not only the investment managers covered in our sample are interested in the topic but also, a much broader audience.

There are now a range of examples of  whereby AI is creating value added propositions for established investment managers. All being said, the aforementioned institutions have all integrated AI technologies into their front office or middle office or  back office functions. While the adoption of AI may not lead to a revolutionary overhaul yet, it can bring about substantial enhancements and improvements in operational efficiency, decision-making capabilities, and client services.

The current industry snapshot shows that the leading players are embracing AI technology for low-hanging fruit rather than aiming for a disruptive change of any function in the value chain. For example, rather than leveraging AI to revolutionize the entirety of investment management functions, certain large players have opted to utilize AI specifically for tactical enhancements in investment research. Additionally, exhibit 3 outlines the live use cases we see in the market that counter some of the scepticism expressed in the ESMA report.

Although AI may still be considered a buzzword for the majority of the industry, it would be hasty to dismiss its potential. The leading firms demonstrate that even incremental advancements through the adoption of AI can shape the investment management value chain. For example, a large US-based manager has implemented over 300 cases of AI in its processes – enabling  them to drive operational efficiencies.

Similarly, Alpha observes that AI is becoming a relatively feasible option for medium and small players that cannot afford costly AI initiatives or fintech acquisitions.

While a few established players in the investment management industry have effectively incorporated AI into their operations, other players are in the early stage of AI adoption. Despite scepticism from major regulatory bodies, we believe that the growing number of AI-as-a-service offerings and the increasing number of AI-skilled workers may enable the rest of the industry to close the gap with the frontrunners and benefit from the AI technology. In parallel, firms need to address the challenges associated with AI implementation, including data management and maintaining effective human oversight as well as upskilling management to stay compliant and prevent harm to clients and the company.

The future of investment management is data and automation driven, and despite AI currently being used mainly for tactical solutions, investment managers who start adoption now will have a head start in developing strong AI capabilities. With the industry starting to experiment with AI, there are lots of opportunities for firms to enhance their AI capabilities.