Can AI outperform a wealth manager at picking investments?

When technology entrepreneur Edward Morris participated in the $5bn initial public offering of chip designer Arm last September, he adopted an entirely artificial intelligence-based strategy that would result in one of his most profitable investments to date.

Morris — who runs the consultancy Enigmatica, specialising in AI and prompt engineering (the creation of chatbot inputs that return the most desirable answers) — says he conducted all the necessary due diligence on his investment using the popular AI-powered virtual assistant ChatGPT and made a 30 per cent return. He typically closes out at 10 per cent.

In the past, Morris might have asked a human financial adviser to help with his investment activities. But, he considers these services “incredibly expensive” and, seeing first-hand the advancement of AI over the past few years, he was keen to try a new approach. He has no regrets.

Morris claims that the chatbot — while, essentially, only a text generator — can improve his understanding of complex wealth management and finance topics, helps him find worthy investments such as the 2023 ARM listing and identifies discrepancies in his bank statements, just like a human financial adviser would.

Additionally, Morris has linked AI tools to his WhatsApp and Telegram accounts so that he is alerted to investment opportunities via text message. Morris adds: “ChatGPT has given me a financial adviser in my pocket at all times that I can talk to and get advice from.”

Simplifying the due diligence process

Reflecting on his ARM investment, Morris says that the way he uses AI in his investments is “unbelievably simple”. He says his first step is to find an investable stock. Then, he undertakes due diligence by firing questions to ChatGPT about the company’s history, current activities, financials and any negative press.

Morris says the AI-powered chatbot will then summarise this information and provide a rating on how well a stock might perform, helping people “make educated investments” without having to shell out large sums of money on a professional wealth management firm or expert.

“Due diligence is something that used to take days upon days to do within wealth management and financial firms. That’s not the case any more with AI,” he explains. “Ninety nine per cent of the investment game is knowing if something is a good investment and ChatGPT seems to be absolutely incredible at creating that information and communicating it in different ways.”

Wealth managers’ second pair of eyes

While AI is not yet a proven tool for individual investors, Morris believes that wealth managers can also benefit from the technology. He says it allows wealth managers to “run their ideas past an extra set of eyes” and complete “time-consuming” tasks such as client risk-profiling questionnaires.

They can also use it for helping clients get their estates in order, assessing the potential impact of economic policies and finding sector-specific investment opportunities, he claims. With these varying use-cases in mind, he urges wealth managers to upskill in AI and prompt engineering to get the most out of the technology in their day-to-day roles.

“If you’re a wealth manager, I’d say learn how to use ChatGPT properly and effectively. Don’t just play with it for a bit and leave it. Give it time,” advises Morris. “It can (and does) save people weeks’, and sometimes months’, worth of time.”

Streamlining wealth managers’ workloads

Sensing the looming AI revolution and its impact on the financial services sector, many of the biggest wealth management groups are already investing in this technology. For instance, Morgan Stanley has developed and rolled out an AI assistant designed to streamline the day-to-day tasks of its global wealth managers.

Powered by OpenAI’s large language model technology, the AI @ Morgan Stanley Assistant allows the bank’s financial advisers to find relevant information from an internal database of more than 100,000 documents.

One such financial adviser is Patrick Biggs, who explains that the chatbot enables him to “efficiently source and retrieve internal information” and summarise corporate processes so that he can spend more time with clients. “Before this technology, I’d have to wade through PDFs and documents of research to find what we needed, which was especially difficult because procedures can evolve, and the markets change every day,” he says.

Sal Cucchiara, chief information officer and head of wealth management technology at Morgan Stanley, says the success of this technology depends on several factors. “One, quality of the data used is critical,” he stresses. “Two, [you need to] engage with the end user early in the process in addition to educating and partnering with teams across the organisation,” he says.

“Lastly, take a control-forward approach to the rollout and work hand-in-hand with legal, risk and compliance partners through every step.”

Improving the human touch

As AI continues to automate many aspects of wealth and investment management, a growing concern of wealth managers is whether it will one day take their jobs. But Mohamed Keraine, global head of digital, wealth and retail banking at Standard Chartered, does not think industry workers should fear the rise of AI. He views the technology as an “opportunity to complement human attributes” rather than “replace them”.

In particular, he expects AI to help wealth managers form stronger relationships with their clients by delivering enhanced, seamless virtual interactions and improving access to wealth management services. For instance, like many other banks, StanChart offers a 24/7 customer service chatbot in addition to a chat and collaboration tool called myRM. The latter allows users to chat with their relationship managers, transfer documents and files securely, and more.

“[AI] will uncover a lot of opportunities in the way we offer advisory solutions and enable quicker and more accurate access to market insights and trends,” he says. “[AI] will also drive a more proactive understanding of customer needs and an unprecedented ability to offer personal, instant and differentiating wealth solutions.”

John Mileham, CTO at online financial adviser Betterment, agrees that AI presents opportunities for both wealth managers and their clients. He explains that Betterment uses AI chatbots externally to answer customers’ questions and requests “more quickly”. And, internally, he says, AI is enabling the firm to automate manual processes ranging from the creation of meeting summaries and marketing copy to fixing software problems. Employees can then focus on “more strategic work”.

Zac Maufe, global head of regulated industries at Google Cloud, says wealth managers can use AI tools to analyse large volumes of client data — such as their financial history and goals, tolerance to risk and demographics — and use this information to develop more personalised investment plans and portfolios for customers.

“Through continuous monitoring and real-time adjustments, AI can ensure clients stay on track towards their financial goals while advisers gain deeper insights to foster stronger relationships and offer relevant products and services,” he says.

Other AI use cases for wealth managers include automated trade execution, the automation of repetitive work, fraud detection, portfolio optimisation and real-time market insights, he adds.

But, regardless of all these advancements, Maufe says wealth managers will still need to strike a balance between AI usage and “the human touch”. He says: “Leveraging AI to enhance, not replace, the human element of wealth management is important since clients still value personalised advice and trust built through relationships.”

Risks when using AI for advice

Although AI is improving the efficiencies of wealth managers and allowing people to access financial advice 24/7, this technology is not without its challenges when actually applied to financial advice or decision making.

A major concern is whether AI may provide bad investment advice that results in users losing large sums of money. For example, Bloomberg reported in 2019 that Hong Kong-based entrepreneur Samathur Li Kin-kan lost $20mn when he used a robo investor service.

Such problems could now be exacerbated by so-called AI hallucinations, in which chatbots generate false or entirely fictitious results. Mileham explains that these hallucinations, as well as other biases, can stem from the chatbots’ underlying training data sets.

“Investors should be very careful to evaluate the source of the financial advice they are relying on,” he warns. “Generative AI is trained on massive data sets that go beyond good investing advice. It could draw incorrect inferences from inputs, and it might not guide you towards optimal strategies.”

Neil Sahota, co-author of Own the AI Revolution and an AI adviser at the UN, warns that AI systems often provide poor investment advice due to “limited personalisation” and a “lack of human empathy”. He explains that AI wealth managers are powered by standardised algorithms that “may not fully account for the nuances of individual financial situations”, such as “specific tax implications” and “unique financial goals”.

Sahota adds that these platforms often “lack the human touch essential to building trust and providing emotional support during volatile market conditions” and that human wealth advisers are best equipped to “offer reassurance and personalised advice”.

Robo investors are also susceptible to cyber attacks and technical issues, which can lead to data leaks and investment disruption, he warns.

Because AI systems are typically trained on legacy data, Sahota suggests that they may also struggle to make decisions during “unprecedented market conditions”. He says: “AI algorithms excel in stable environments but may struggle to adapt quickly to sudden economic shifts.”

Adam Rodriguez — director of product at autonomous car technology company Waymo and an Arta Finance customer — agrees that AI wealth managers may sometimes respond to an investment scenario in “an unexpected way” because this isn’t reflected in their training data.

However, he suggests that “established and proven” AI investors are better equipped to deal with this issue and, consequently, advises people only to “invest with reputable firms who have designed the system and built in the proper safeguards”.

A bright future

Concerns aside, it seems robo investors have a bright future. In particular, the rise of agentic AI systems could allow robo investors to mimic the proven and winning strategies of businessman and investor Warren Buffett, suggests Nell Watson, an AI expert and author of Taming the Machine: Ethically Harness the Power of AI.

She argues that agentic AI systems — which use their own autonomy to set and meet complex goals with little human input — would be able to “uncover key insights and patterns” by analysing large volumes of financial reports, market trends, news pieces and other reading materials at “incredible speeds”.

“Just as Buffett dedicates five to six hours daily to reading 500 pages, these AI systems can continuously ingest and analyse data 24/7, giving them an even more comprehensive and up-to-date knowledge base,” she argues.

AI algorithms excel in stable environments but may struggle to adapt quickly to sudden economic shifts

Aside from content consumption, Watson believes that the technology could also one day be capable of deciphering the variables responsible for “market dynamics” and “company performance”.

“Using sophisticated machine learning algorithms and predictive modelling techniques, these systems can identify subtle correlations, curious anomalies, and forecast future trends with a high degree of accuracy,” she says. “This allows them to spot undervalued ‘diamonds in the rough’ with strong fundamentals and growth potential — the very essence of Buffett’s value investing approach.”

However, acknowledging common concerns, she says this will depend on high-quality training data and underlying algorithms in addition to “robust” risk management frameworks and human oversight.

Watson’s belief in this technology is unwavering, though. She concludes: “The potential is immense — just as Buffett has used his reading habit to build an unparalleled investment record, agentic AI’s independent data processing capabilities could turn a small family office into the next Berkshire Hathaway, revolutionising the world of finance. The rise of the AI-powered ‘super-investor’ may be closer than we think.” 

This article is part of FT Wealth, a section providing in-depth coverage of philanthropy, entrepreneurs, family offices, as well as alternative and impact investment