Wealthy clients will always value human advisers over AI

If implemented properly, AI should help wealth managers rather than replace them, freeing them up to focus on clients, said a panel at PWM's recent Innovation in Wealth Management Summit.

There is no doubt that artificial intelligence (AI) will transform wealth management, but will it ever replace the human adviser?

This was a key question debated at the recent PWM’s Innovation in Wealth Management Summit 2024. Investment professionals argued that technology powers, or augments, advisers and portfolio managers, but humans will always remain in the loop, especially because this is what clients want.

“Our output is a lot more than a computer output, it is empathy, advice and understanding,” said Fahad Kamal, chief investment officer of Coutts, a leading UK private bank known to be close to the Royal Family.

“Throughout history, technology has augmented private bankers and will not replace us for the foreseeable future; we offer an enormous value proposition,” he added.

If wealthy clients were asked if they would like AI or human beings to look after their affairs, 100 per cent of the time they would choose a human being, he said.

There are going to be fewer portfolio managers in the future, conceded Mr Kamal, but they will probably be better at their jobs. “There's going to be a period of shift and churn, but we will end up in a better equilibrium than we are now, as a society and as an industry.”

AI has many use cases in wealth management already and is expected to further impact portfolio management too. “AI is making our jobs better, our risk management is undeniably better because we employ AI tools,” said Mr Kamal.

For instance, AI helps portfolio managers analyse huge amount of information in a digestible format which is “light years ahead of where we were five years ago”. It can identify whether portfolios are “out of synch” with strategic asset allocation and the impact of macro-economic conditions. Understanding factors that drive portfolios improves products and risk management, which leads to better returns, he said.

Improving risk management is vital also because the role of a portfolio manager has evolved enormously over the past two decades, said Norman Villamin, group chief strategist at Geneva-based Union Bancaire Privée. In the past, portfolio managers focused on their home market only. “Today they are asked to become global investors, with a global data set, which they do not have time to analyse. AI is helping portfolio managers to manage risk better.”

Moreover, the world is getting more complex, and 90 per cent of the data available today has been created over the past few years. This huge amount of data can no longer just be processed by the human brain, said Céline Le Cotonnec, chief data officer at Bank of Singapore

Front offices and portfolio managers need to carry out a greater number of tasks before making a recommendation to the client, she said, taking in the impact of more regulation on data protection and sustainability, for instance.

“Technology and AI can empower people to be compliant, while still not forgetting we have to serve the client. We should spend more time with clients, rather than being in the background and doing compliance checks,” she told the summit.

Data lake

One of the areas of portfolio management that will most benefit from AI is personalisation.

“Where AI can support in uplifting the customer experience is when it comes to discussing the performance of their portfolio and where it's coming from, in detail, being able to deep dive in a more hyper-personalised experience with the client. This is something that portfolio managers do not have time to do,” said Ms Le Cotonnec.

They still need to review the commentary, she said, but reviewing and proofing is much quicker than writing it.

This is an example of how technology will lead to automation of tasks, rather than job losses, and change of roles, with new skill sets being required, she said, highlighting several studies on this topic, including research from consultancy McKinsey

AI is challenging one of the key principles of the industry, which is “trying to standardise to scale, and centralise to scale”, said Elliott O'Brien, head of business transformation at LGT Wealth Management, UK. “A personalised approach is incredibly difficult to scale, but with the advent of AI, there is an opportunity for that to be turned on its head,” offering that “kind of hyper personalisation at scale, which clients want.”

“The amount of time that client facing teams are spending on activities that deliver value to clients is low, or lower than we'd want it to be. If you can push that forward with AI, we are going to have potentially hugely positive results,” said Mr O’ Brien.

While it is difficult to foresee how roles will change in the future “people trust people, and I can't see that ever changing”, he added.

Job dislocation

David Shrier, professor of practice, AI and innovation, Imperial College Business School brought a different perspective. His analysis on the impact of AI on the economy and financial services, conducted in 2023 with Evercore ISI’ s chief strategist Julian Emanuel, shows that within asset management, 50 to 80 per cent of jobs will be impacted by AI.

This is partly due to the fact that people will work with their “AI copilot”, integrating AI into their workflows and processes, but also because jobs will disappear due to AI.

“The portfolio manager, the wealth manager, the client relationship manager is going to have an AI buddy, constantly feeding them critical information at the moment they need it, and helping their clients solve complex problems,” he said.

Established financial institutions globally could be looking at $30tn of incremental market cap from revenue growth related to AI, by 2032, but there will be jobs dislocation. A large private bank has recently hired an executive as “senior vice-president of Chat GPT, with the aim of firing 30,000 customer service agents and replace them with GPT,” reported Mr Shrier.

“We do need to learn new things faster and be ready for the AI enabled job of the future rather than hoping we can just slightly change our existing job. We also have the opportunity to dramatically grow revenue and GDP.”

But the biggest barrier to harvesting revenue gains is “mindset shift and human resistance to change”, he added.

No magic bullets

Another big challenge around AI is data governance and legacy systems. “As an industry, we're still trying to get data in the right place because ultimately without that foundation, it's sort of talking about a bathroom with no plumbing,” said LGT’s Mr O’Brien.

AI is today used in areas such as automation, portfolio management, research analysis where there is control over the data set, and AI is proving an “incredibly powerful tool”.

But this is the “low hanging fruit. To elevate that to the client experience it is going to take time, because you must have absolute faith in your data set.”

Bank of Singapore’s Ms Le Cotonnec stressed the importance of data literacy and education.

“One of the issues I have seen in wealth management, and banking in general, is the lack of access to data and lack of understanding data. Too many times I hear people think, ‘Our data quality is not good’. But a lot of times it's lack of education and understanding on how the metrics are created, it is about how to interpret data,” she said.

Bank of Singapore has created a platform with “a curated set of clean data, understandable with a dictionary, available to everyone”.

A growing risk to monitor is that advisers are losing touch with data, said UBP’s Mr Villamin. Young analysts today are looking at “finished output” by models, as opposed to understanding how data has combined to result in an output. “We're losing sight of the visualisation of the data underneath it, which is one of the keys in terms of risk management,” he said, recalling that when he started in the industry, the job of new analysts was to collect data, with pen and paper, to understand “how that data makes it all the way through the decision chain”.

“We're distancing ourselves from the raw data, we don’t understand data enough and we're losing touch with it. This creates more left tail risks than we understand.” That left tail risk – that private bankers lose their money – is what wealthy clients most worry about, he explained.

But AI should not be seen as a magic bullet. “Even with the greatest AI tools on earth, the [portfolio management] job is about predicting the future, and there is no data set for that,” said Coutts’ Mr Kamal. “A lot of it ultimately comes down to judgement and even before judgement, it comes down to philosophy and faith, in how you expect the world to unfold over the next one, five or 10 years,” he said.

“That's the very crux of why our relevance will continue to be huge, because clients are going to follow people whose faith and philosophy they believe in, when it comes to investing.”