While asset and wealth managers are all gradually deploying AI to replace some human processes, their endgame must involve more client interaction if they are to succeed

Portfolio management for wealthy clients has entered a major transition, according to leading tech players, with artificial intelligence playing an increasing, though not yet pivotal role.

“AI is currently transforming processes, data analytics, computing speed and, to some extent, improving our ability to extract insight from very large, inter-connected datasets,” says Stuart Cash, founder and CEO of the Y Tree wealth tech platform, aimed at high net worth individuals and their families.

Cash founded the firm, which he dubs “the CIA of wealth management” in 2017, because in his talks with clients of the banks he previously worked for — including SG Warburg and Goldman Sachs — the feedback was that the ideal service did not exist. The formula which he strives to provide, involves “combining data, experience and technology” to help shape client portfolios.

The addition of AI, he believes is improving “significantly in some areas” the tech-led services already provided by a small group of wealth and asset managers. What has changed today, as the industry approaches an inflection point, is the sheer scale of the process.

“What we are seeing is larger datasets, more powerful machines and models that are far more complex and better at finding patterns,” suggests Cash. “The cynical would say that they are building better guessing machines.”

Systematic trading

AI has only become widely accessible to portfolio managers and advisers during the last two years, despite machine learning having been around for 40 years. Indeed, Cash is a big fan of the late James Simons, a mathematician turned cold war codebreaker, who in 1982 founded Renaissance Technologies, a New York-based systematic trading house running $130bn.

“There will be good models and bad models, so some firms will still stand out,” he says. “But for now, AI is primarily an accelerator of operational and analytical efficiency in asset management, which is a positive development.”

Much as the internet and software like email, excel and powerpoint redefined many asset management jobs in the last 1990s and early 2000s, he expects the future of certain roles and size of teams to be called into question by the latest AI wave.

“Will it be similar to how robotics has transformed the car industry? Maybe, for some roles that are purely about collecting and analysing data and producing codifiable tasks, it will,” he suggests. “But it will certainly open the door to new roles, too.”

A further AI-led revolution, he believes, will enable deeper hyper-personalisation, built around behaviours and preferences learned by agents known as “copilots”. Wealth firms will also enjoy better governance, coupled with ability to build specific models to serve their client base. “This will give organisations a safer and more differentiated way to deploy AI at scale,” says Cash.

Much basic portfolio management is already “heavily commoditised”, he says, accommodating growth of index products such as ETFs, which have simplified investment into more transparent, economical and efficient strategies.

Asset managers have already adjusted to this, but it hasn’t eliminated the market for what Cash calls “premium access”, where the promise of outperformance justifies higher fees and less transparency. “That is unlikely to disappear,” he says.

Wealth managers face much greater and more immediate pressures in how their client portfolios are overseen, believes Cash.

AI-powered models

“The traditional value proposition — selecting where and how to gain investment access — is now deeply challenged,” he says with AI-powered models directly confronting the business case. “If a well-built model can analyse vast data sets and conclude that, in many cases, the optimal choice is to hold the index, then a large part of the historical differentiation falls away.”

Offering a set of investments or client service strategies different to the rest of the market has become a major objective which many players struggle with.

“I do think differentiation is an industry challenge, and I think it’s been there for quite a while, and I think now, with the ability for AI to take on some of these business processes, it becomes even more of a bigger threat and a concern,” says Kerry Ryan, senior director at Seismic, a US tech provider for wealth and asset managers.

“That’s why the smart companies are thinking intentionally around, what do they stand for, and where do they place their bets in terms of what capabilities they’re going to deliver to the market.”

“Many managers claim their portfolios are 90 per cent sustainable, so while it’s still a topic, it’s no longer differentiating one bank from another one,” says Fabienne Mailfait from We Wealth

Sustainability was one key differentiator of portfolio managers, but its role has been fading since the anti-climate change lobby in the US has been gaining ground. “This has been one of the main topics for the last 10 years,” says Fabienne Mailfait, CEO and founder of Italy’s We Wealth platform, which brings together asset managers, family offices and advisers.

“Many managers claim their portfolios are 90 per cent sustainable, so while it’s still a topic, it’s no longer differentiating one bank from another one.”

Investment views, which allow banks and their clients to stay more informed than “normal news”, particularly around geopolitics, are however attracting investors to portfolio managers perceived as experts in this discipline, able to demonstrate “a really strong conviction, which makes a difference”, she believes.

 Searching for the Holy Grail

Private banks are already struggling to redefine portfolio management propositions, which must not only make use of the vast data sets which Cash talks about, but also incorporate client behaviours into their model. This is seen as the Holy Grail of wealth management for the 2030s.

“By 2030, success in wealth management will belong to those firms who help clients make the best decisions consistently,” he predicts. “AI will enable the creation of a personalised ‘intelligence engine’ — an always-on, real-time system tuned to an individual’s life,” overseen by “expert facilitators capable of navigating family dynamics, next generations, partners and behaviours”.

This is an issue that all service providers keep coming back to. “Some banks are looking at this as a holistic problem,” says Singapore-based Laksh Gangwani, chief growth officer at ViewTrade, who spends much of his management time preparing for what he calls an $80tn shift from boomers to Gen Z and millennials.

Financial firms are still coming to terms with the new challenge, he believes. “Digital-native investors expect intelligence, not paperwork,” as they enter what he calls the “age of cognitive abundance”, where AI handles micro-decisions and advisers focus on strategy, empathy, and personalisation.

Institutions which fail to embrace this shift risk losing the next generation entirely. Some banks are investing in projects to meet this challenge, he reports.

 Product-pushing mindset

“They are trying to say that if a client owns Nvidia’s stock, what is the affinity of that with other products we can sell them? So it is a very product-led mindset that is still there,” says Gangwani.

Rather than using technology to help clients manage their portfolio more effectively, they scan clients’ holdings for stocks and products. “Then they ask: ‘What is the most high affinity product that we can now put in front of this client so that they can push the button and buy this?’ Is this a hyper-personalised approach? Yes, but is this client centric? I’m pretty sure everybody can debate that, but my point is that all of these efforts are still driven from a product perspective.”

“Digital-native investors expect intelligence, not paperwork,” says Singapore-based Laksh Gangwani of ViewTrade

This emphasis on analysing data means leaders of banks and wealth managers are increasingly emerging from the technology sphere, says Gangwani. “You look at any acquisition today and it’s all about platforming services,” he says, particularly when it comes to democratising access to private assets, now seen as a core strength for any leading wealth manager.

“I remember seeing how technology was always at the periphery, but as it is becoming core, we have seen how decisions are taken differently, and that has proved a pretty amazing experience…you know, you can democratise intelligence, you can democratise access, you can democratise great outcomes,” he says, using AI to build portfolios utilising direct indexing strategies. “Technology has the power to do that.”

 Culture shock

Even those wealth managers who claim to be very advanced in this grand technological transformation still have a long way to go, although a “brave new world” of wealth management has been developing since the end of the Covid-19 pandemic.

“When we pitched three years ago, nobody was listening,” admits Manuel Grenacher, CEO of Unique, which provides AI services for wealth managers. “I would say, to be honest, it was very tough.”

Wealth firms would sign an agreement with tech providers, but their advisers often took some persuading to use portfolio management and data mining tools. Changing the internal culture of client firms is typically harder than initially persuading a bank to use advanced technological innovations, believes Grenacher.

“It’s not a technology game, it’s all about adoption,” he says. “Look at UBS and other larger players, who see it as more of a technology game. They partner up with Microsoft and expect to see a big bang. But these giant tech actors, the horizontal players, are really far away from the industry and they find it hard to encourage adoption.”

What particularly surprised him was the backwardness of some leading US wealth managers. “There are various company cultures, and some are moving faster than others. When we started in the US, in New York, I had the feeling they must be ahead. But it’s not true. Even their adoption is sometimes slower than the Swiss banks, so I think we still have a huge opportunity.”

For most banks which embrace increased use of AI and digital services, the main goal is improving profitability.

“It’s true today that the solutions are helping us more on efficiency gains, rather than building your next financial model to outperform,” says Manuel Grenacher, CEO of Unique.

“The biggest fight we have in Switzerland and the same here in London is the cost-income ratio,” says Grenacher, who has worked with wealth firms including LGT and Pictet, enabling them to enhance research, compliance and know your customer services.

Since Unique started work with Pictet, the Geneva-based bank reports time savings of two hours per week for each employee, reveals Grenacher, no stranger to entrepreneurship, having previously built and exited multiple tech companies, including Coresystems, acquired by SAP, and Mila, acquired by Swisscom.

While he clocked an “80 per cent adoption rate” for advisers at LGT, it was the Pictet “super good role model” which he was particularly pleased with.

Although Pictet has the image of a conservative and “traditional Geneva bank”, their advisers are “fascinated by the AI technology in general, knowing they can get a better customer experience when they use those technologies”, he says.

Rather than fearing that AI will make their roles irrelevant, bank advisers are more likely to “fear they may be potentially replaced by another employee who understands better how to use the technology”.

It is no secret that the main aim for many banks embracing AI is cutting costs to improve profitability, rather than acting in the best interest of clients, admits Grenacher.

“It’s true today that the solutions are helping us more on efficiency gains, rather than building your next financial model to outperform,” he says. Although it’s not too early to use AI for portfolio management, most wealth firms are not yet using the technology for this purpose, says Grenacher, whose team focuses on working with wealth managers with more than €100bn in client assets. Smaller players running €10bn in private equity funds are also targeted.

“They use AI for client experience, for efficiency gains, and that is tremendous already,” he says. “It’s quite sustainable, as firms can serve thousands of clients per week, which pays into cost-income ratio optimisation.”

 Human factor

But despite this new tech-led approach being pioneered by leading players, those who cut back too far on human resources are likely to suffer, he believes. “My personal view is that in financial services, the human is still a key fator in decisions, because empathy is still missing from AI,” he says. “I would always start with hiring the front people who build the human relationships.”

As well as investment management, the research  which helps clients position and tilt their portfolios is also key and one of the low-hanging fruits, according to Grenacher, with little of it tailored to the needs of individual families.

“What I hate is when a bank sends me just the same house view that everyone gets, and I still get from some banks, the house view every month, completely not tailored to me, 90 per cent of which I am not interested in,” says Grenacher, believing that technology has much to contribute in this sphere.

“They need to give us more tailored information or research and also get us more access to their network. Together with AI, you could supercharge the human to serve the client relationship much better.”