Alan Turing, the father of computing, posited a theory for when he believed we would know generative computing tech had advanced to the level of human intelligence. What he called the ‘Imitation Game’ theory – now known as the ‘Turing test’ – suggests that, if a piece of programmed software can convince a human it is also another person, then machines could be considered to have general intelligence.
It is well-documented that artificial intelligence (AI) can now convincingly impersonate a human – although there is still a hesitance to suggest it possesses human intelligence. So how can it be developed enough to pass Turing’s test, yet not to satisfy its conclusion?
AI is good at taking data, integrating it and producing the most probable outcome – what is called ‘narrow intelligence’. This is why sometimes, when we interact with so-called large language models (LLMs), it can feel almost as if we are talking to an actual person – it is excellent at responding with the most likely set of words that should follow.
Nevertheless, AI lacks a core element of what people value in their interactions with each other – emotional intelligence and that hard-to-define yet so important, human touch. Still, is there a growing tech frontier where the two worlds can converge?
In wealth management and broader financial advice, there has been an understandable reticence due to the notion AI could do us all out of a job. Even so, that does not mean it will not become a very useful tool in our work going forward. According to the recent State of the Advice Nation report from the lang cat, more than a quarter of advisers (29%) surveyed said they were adopting AI in the workplace, with a further 34% saying they expected to be adopting it in the next five years.
It would be foolish to assume AI will have no role to play going forward – of course it will. As such, there is considerable value in considering how wealth managers might best use it along with their own ‘human touch’ services to improve client outcomes.
More time to advise
What if we think of AI as a way to enhance the work we do? Leaving aside some of the inevitable challenges to consider where its core strengths lie, we can see there is a glaring opportunity for ‘AI assistants’ supporting superpowered advice.
If there is an area AI tends to shine, it is performing repetitive and time-consuming tasks. An adviser could use an ‘AI assistant’ for meeting transcriptions, paperwork processing, factfinding and planning. We have already seen some great developments of AI-based tech that supports these tasks.
Now, the clue is in the word ‘assistant’. To maximise efficiency and help prevent errors, wealth managers and other financial advisers will need to keep a professional eye on the AI’s work. Assuming a good advice firm would be across this, however, then their time should be freed up and workload reduced – allowing them to refocus more attention on advising and less time on faff. At Aberdeen, for example, we are actively testing out agentic and chatbot capabilities to enable faster and more accurate responses for advice firms to drive efficiencies and enhance satisfaction of our services.
“To maximise efficiency and help prevent errors, wealth managers and other financial advisers will need to keep a professional eye on the AI’s work
So here is the big question - could some of these fast-developing AI assistant functions help close the UK’s oft-mentioned advice gap?”
So, with the number of people receiving financial advice reducing and 75% of advisers saying clients with less than £100,000 of investable assets are challenging to serve in a profitable and compliant manner, here is the big question – could some of these fast-developing AI assistant functions help close the UK’s oft-mentioned advice gap?
Well, there has to be a real opportunity here – both for the advice profession and for potential customers who have – to date – fallen through the gaps. The opportunity is for AI to help the advice profession support more consumers as they look for new and convenient ways to better grow their wealth, engage with their finances and plan for later life.
Security concerns
Despite the obvious efficiencies of AI, there are still understandable and real concerns about the security of sensitive information. AI, such as LLMs, learn and become more powerful by swallowing up all the data it has been fed in order to train itself. Depending on the product being used, data is sometimes shared or pooled, which could leave client information at risk of being exposed externally.
This will require due diligence from the adviser to be sure that an AI they are using for assistance is secure with its data. It will also require fintech companies with AI offerings to be absolutely transparent about their data policy, if they want advice professionals to use it.
Again offering Aberdeen as a case study, we are currently focussed on automation and connectivity in data. We also have work underway to connect platform data with customer relationship management tools and integration portals. The aim is to be the most connected and integrated platform, supporting wealth managers and advisers to access their clients’ data where and when best suits their process.
AI has advanced at a startling rate over the past couple of years – during which time there have been an increasing number of headlines screaming about its inevitable takeover. It is, however, a far more nuanced and less nihilistic picture than many of these headlines would lead us to believe.
The use of AI in wealth management and planning in the coming years will no doubt proliferate, but we are unlikely to see the human touch done away with any time soon. If used properly and responsibly, it is this technophile’s considered opinion that AI could prove a tremendous boon for the wealth and financial advice sectors and the clients we all serve.
Derek Smith is chief technology officer at Aberdeen Adviser
AI and client vulnerability
One area the human touch almost certainly wins out over AI in investment and financial advice is in dealing with vulnerable clients, whose issues may be affecting their financial decision making. According to recent research from the Financial Conduct Authority, more than a third (37%) of clients in vulnerable circumstances reported embarrassment as a reason for not disclosing personal situations.
Read more on this subject here: The changing nature of client vulnerability
A focused adviser would perhaps be able to recognise if any material changes in a client’s financial behaviour – along with social clues – could indicate a client’s vulnerability and be able to approach the question sensitively and responsibly. AI, if it spots it at all, may not be able to communicate sympathetically – either leaving the issue unresolved or the client feeling distressed.
More constructively, however, AI can be trained to scan sentiment across all channel interactions – telephonic, digital and so forth – to help spot vulnerability red flags, which can then be communicated to the adviser for consideration. This is something we are actively testing to enhance our understanding of how we spot and deal with potential customer vulnerabilities and better support our wealth manager and financial adviser clients.
