When technology entrepreneur Edward Morris participated within the $5bn initial public offering of chip designer Arm last September, he adopted a wholly artificial intelligence-based strategy that may lead to one among his most profitable investments thus far.
Morris — who runs the consultancy Enigmatica, specialising in AI and prompt engineering (the creation of chatbot inputs that return probably the most desirable answers) — says he conducted all of the obligatory due diligence on his investment using the favored 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 need asked a human financial adviser to assist along 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 brand 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 resembling the 2023 ARM listing and identifies discrepancies in his bank statements, identical to a human financial adviser would.
Additionally, Morris has linked AI tools to his WhatsApp and Telegram accounts in order that he’s alerted to investment opportunities via text message. Morris adds: “ChatGPT has given me a financial adviser in my pocket in any respect times that I can seek advice from and get advice from.”
Simplifying the due diligence process
Reflecting on his ARM investment, Morris says that the way in which he uses AI in his investments is “unbelievably easy”. He says his first step is to search out an investable stock. Then, he undertakes due diligence by firing inquiries to ChatGPT in regards to the company’s history, current activities, financials and any negative press.
Morris says the AI-powered chatbot will then summarise this information and supply a rating on how well a stock might perform, helping people “make educated investments” without having to shell out large sums of cash on an expert wealth management firm or expert.
“Due diligence is something that used to take days upon days to do inside 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 investment and ChatGPT appears to be absolutely incredible at creating that information and communicating it in alternative ways.”
Wealth managers’ second pair of eyes
While AI just isn’t yet a proven tool for individual investors, Morris believes that wealth managers can even profit from the technology. He says it allows wealth managers to “run their ideas past an additional set of eyes” and complete “time-consuming” tasks resembling client risk-profiling questionnaires.
They can even use it for helping clients get their estates so as, assessing the potential impact of economic policies and finding sector-specific investment opportunities, he claims. With these various use-cases in mind, he urges wealth managers to upskill in AI and prompt engineering to get probably the most out of the technology of their day-to-day roles.
“If you’re a wealth manager, I’d say learn tips on 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’, value of time.”
Streamlining wealth managers’ workloads
Sensing the looming AI revolution and its impact on the financial services sector, lots of the largest wealth management groups are already investing on 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 search out relevant information from an internal database of greater 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 in order that he can spend more time with clients. “Before this technology, I’d need to wade through PDFs and documents of research to search out what we wanted, which was especially difficult because procedures can evolve, and the markets change each day,” he says.
Sal Cucchiara, chief information officer and head of wealth management technology at Morgan Stanley, says the success of this technology relies on several aspects. “One, quality of the info used is critical,” he stresses. “Two, (it is advisable) engage with the tip user early in the method along with 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 points of wealth and investment management, a growing concern of wealth managers is whether or not it would someday take their jobs. But Mohamed Keraine, global head of digital, wealth and retail banking at Standard Chartered, doesn’t think industry employees should fear the rise of AI. He views the technology as an “opportunity to enhance human attributes” somewhat than “replace them”.
In particular, he expects AI to assist 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 support chatbot along with a chat and collaboration tool called myRM. The latter allows users to speak with their relationship managers, transfer documents and files securely, and more.
“(AI) will uncover plenty of opportunities in the way in which we provide advisory solutions and enable quicker and more accurate access to market insights and trends,” he says. “(AI) can even drive a more proactive understanding of customer needs and an unprecedented ability to supply personal, quick and differentiating wealth solutions.”
John Mileham, CTO at online financial adviser Betterment, agrees that AI presents opportunities for each wealth managers and their clients. He explains that Betterment uses AI chatbots externally to reply customers’ questions and requests “more quickly”. And, internally, he says, AI is enabling the firm to automate manual processes starting from the creation of meeting summaries and marketing copy to fixing software problems. Employees can then concentrate 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 — resembling their financial history and goals, tolerance to risk and demographics — and use this information to develop more personalised investment plans and portfolios for purchasers.
“Through continuous monitoring and real-time adjustments, AI can ensure clients stay heading in the right direction towards their financial goals while advisers gain deeper insights to foster stronger relationships and offer relevant 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, no matter all these advancements, Maufe says wealth managers will still have to strike a balance between AI usage and “the human touch”. He says: “Leveraging AI to reinforce, not replace, the human element of wealth management is vital 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 just isn’t without its challenges when actually applied to financial advice or decision making.
A serious concern is whether or not AI may provide bad investment advice that ends in users losing large sums of cash. 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, through which chatbots generate false or entirely fictitious results. Mileham explains that these hallucinations, in addition to other biases, can stem from the chatbots’ underlying training data sets.
“Investors needs to be very careful to judge the source of the financial advice they’re counting on,” he warns. “Generative AI is trained on massive data sets that transcend good investing advice. It could draw incorrect inferences from inputs, and it may not guide you towards optimal strategies.”
Neil Sahota, co-author of and an AI adviser on the UN, warns that AI systems often provide poor investment advice as a consequence of “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”, resembling “specific tax implications” and “unique financial goals”.
Sahota adds that these platforms often “lack the human touch essential to constructing 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 vulnerable to cyber attacks and technical issues, which might result in data leaks and investment disruption, he warns.
Because AI systems are typically trained on legacy data, Sahota suggests that they can 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 automobile technology company Waymo and an Arta Finance customer — agrees that AI wealth managers may sometimes reply to an investment scenario in “an unexpected way” because this isn’t reflected of their training data.
However, he suggests that “established and proven” AI investors are higher equipped to cope with this issue and, consequently, advises people only to “invest with reputable firms who’ve designed the system and in-built the correct safeguards”.
A vivid future
Concerns aside, it seems robo investors have a vivid 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 writer of .
She argues that agentic AI systems — which use their very own autonomy to set and meet complex goals with little human input — would give you the chance to “uncover key insights and patterns” by analysing large volumes of monetary reports, market trends, news pieces and other reading materials at “incredible speeds”.
“Just as Buffett dedicates five to 6 hours every day to reading 500 pages, these AI systems can repeatedly ingest and analyse data 24/7, giving them a good more comprehensive and up-to-date knowledge base,” she argues.
Aside from content consumption, Watson believes that the technology could also someday be able to deciphering the variables answerable for “market dynamics” and “company performance”.
“Using sophisticated machine learning algorithms and predictive modelling techniques, these systems can discover subtle correlations, curious anomalies, and forecast future trends with a high degree of accuracy,” she says. “This allows them to identify undervalued ‘diamonds within the rough’ with strong fundamentals and growth potential — the very essence of Buffett’s value investing approach.”
However, acknowledging common concerns, she says it will rely upon high-quality training data and underlying algorithms along with “robust” risk management frameworks and human oversight.
Watson’s belief on this technology is unwavering, though. She concludes: “The potential is immense — just as Buffett has used his reading habit to construct an unparalleled investment record, agentic AI’s independent data processing capabilities could turn a small family office into the subsequent Berkshire Hathaway, revolutionising the world of finance. The rise of the AI-powered ‘super-investor’ could also be closer than we expect.”
