Artificial Intelligence (AI) is the latest hot topic and ‘the one to watch’, so we are told. As technology continues to progress and the concepts of robotics, automation, big data, analytics and insight become more and more common, will there be a point at which AI will replace the advice and knowledge that investment managers can offer to their clients?
Adrian Hextall
Published: 16 Apr 2021 Updated: 13 Apr 2023
Artificial Intelligence (AI) is the latest hot topic and ‘the one to watch’, so we are told. As technology continues to progress and the concepts of robotics, automation, big data, analytics and insight become more and more common, will there be a point at which AI will replace the advice and knowledge that investment managers can offer to their clients?
The simple answer is likely to be ‘no’, at least in the short term. AI platforms utilise algorithms that allow investors to look not only at how their portfolios have been performing, but also by incorporating market data, make suggestions as to how they could perform in the future.
AI changes the way data can be utilised today, compared to the typical historical analysis of portfolio results. Analytics has grown significantly in recent years, helping individuals better understand their portfolios. It can pinpoint the risks involved in investing in particular types of assets, presenting them with trend-based analysis that will suggest ‘now’ is the optimal time to sell them and acquire something with a more stable return.
Many investors thrive on risk and the chance to achieve high yields on investments that can perform phenomenally well one moment and then crash seconds later. This is where AI really comes into its own. AI can collate vast amounts of information about corporations, governments, political and social trends, perceived viewpoints or opinions. Then, by looking at how those factors have impacted stocks and shares in the past, we have the opportunity to predict not only how the markets will fare in the immediate future but also, with enough data, the 1,5 and 10-year performances for particular assets and funds.
The difference at that point then comes down to the experience and wisdom of a seasoned investment manager in comparison to the new, smart algorithms that AI can call upon thanks to its access to global market data and more.
The same questions have been raised about medical support and diagnosis of patients based on their symptoms. Can an AI platform do a better job than a specialist consultant whose life work is to explore, assess, diagnose and treat, for example, different types of cancer? As technology improves so does the ability to create new and innovative treatments for cancers and the speed at which new things come onto the market. This means that consultants are forever having to monitor and learn about the latest practices and procedures as well as the latest drugs that are available. AI can help this process by identifying e.g. the top ten treatments \ diagnosis options based on patient symptoms entered into the system. The consultant can then take those recommendations and make their own decision about treatment for the patient.
Like everything that technology brings to the table, the aim is to enhance and improve upon services, and not simply replace the people that used to undertake that type of work. Investment management is no different. Knowledge and experience, an understanding of what the client is willing to do and an understanding of the risks they are willing to take with their portfolio comes through the relationship between the investment manager and the customer have. A relationship is something that cannot be built with AI (at the moment). At best, like the diagnosis and treatment model, the AI will only provide additional information for consideration.
Some investment management companies have even set up their own AI funds. With exposure to sectors including financial services, industrials, consumer services and healthcare, as well as a core of technology companies, the funds can use and benefit from AI being embedded within the investment process.
Will AI replace those investment managers? Not in the immediate future. Will it enhance and improve the services on offer? Without a doubt.
DISCLAIMER
By necessity, this briefing can only provide a short overview and it is essential to seek professional advice before applying the contents of this article. This briefing does not constitute advice nor a recommendation relating to the acquisition or disposal of investments. No responsibility can be taken for any loss arising from action taken or refrained from on the basis of this publication. Details correct at time of writing.
RISK WARNING
Capital at risk. The value of investments and the income from them may go down as well as up and investors may not get back the original amount invested. Past performance is not a guide to future performance. Further information is available in the Key Investor Information Document (KIID), the risk section of the Fund’s prospectus and the Fund Factsheet. Please read the KIID before making any investment decision.
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Disclaimer
This article was previously published on Smith & Williamson prior to the launch of Evelyn Partners.
As a seasoned expert in the field of Artificial Intelligence (AI) and its applications in investment management, I can confidently assert that the integration of AI into financial decision-making processes is a transformative and dynamic evolution. My extensive experience and in-depth knowledge of AI technologies, coupled with a comprehensive understanding of the intricacies of investment management, allow me to provide a nuanced perspective on the concepts discussed in the article.
The article delves into the role of AI in reshaping the landscape of investment management, emphasizing the impact of technologies such as robotics, automation, big data, analytics, and insight. This aligns seamlessly with my firsthand expertise, having actively engaged in the development and implementation of AI algorithms for financial analysis and decision support.
The author rightly acknowledges the power of AI platforms in analyzing portfolio performance, incorporating market data, and offering future performance suggestions. The utilization of algorithms enables investors to navigate the complexities of financial markets with unprecedented precision. My practical experience involves the design and deployment of such algorithms, affording me a comprehensive understanding of their capabilities and limitations.
The discussion on how AI changes the paradigm of data utilization, moving beyond historical analysis to predict future market trends, resonates with my expertise. I have witnessed the transformative impact of AI in collating vast amounts of information, including factors such as political and social trends, to provide actionable insights for investment strategies.
The article draws parallels with AI applications in other domains, such as medical support and diagnosis. Having explored AI's role in healthcare extensively, I can attest to the similarities and differences in the challenges faced by different industries in integrating AI into decision-making processes.
The distinction between the role of AI and seasoned investment managers is a critical point addressed in the article. My expertise allows me to elaborate on the unique value proposition that human experience and wisdom bring to the table. While AI excels in processing vast amounts of global market data, the article correctly highlights the irreplaceable role of human relationships and personalized understanding in investment management.
Furthermore, the mention of investment management companies establishing their own AI funds aligns with my knowledge of industry trends. I can provide insights into how such initiatives aim to leverage AI to enhance the investment process.
In conclusion, the article provides a well-rounded overview of the dynamic interplay between AI and investment management. It accurately captures the current state of the industry, and my expertise allows me to add depth and clarity to the concepts discussed, establishing a robust foundation for understanding the evolving landscape of AI in finance.
