View more on these topics

Can artificial intelligence solve the DB transfer problem?

Pension transfers are a minefield for advisers but the makers of a new tool believe their algorithms can provide the answer

The recent launch of Wealth Wizards’ artificial intelligence capability, Turo, illustrates the possibilities technology can bring to advice. Turo enables robo-advice to be delivered in line with an advice firm’s way of doing things. As a result, it can be applied to more complex areas of advice such as DB pension transfers.

Advice firms input a representative sample of around 20 to 30 DB transfer cases and Turo breaks those decisions down into 18 economic and psychological factors.

“The sample of representative cases gives the computer an idea of what decisions you make and how you make them. This is passed to AI algorithms which figure out under what circumstances DB pensions should be transferred and which factors mean they shouldn’t,” says Wealth Wizards’ chief executive Andrew Firth.

Alan Hughes: Did FCA authorisation process fail British Steel members?

“It“It can also be used as a compliance tool, identifying cases where the adviser may want another look because the advice given may not be expected.”

Commentators describe DB transfers as a “hot potato”, so could AI provide the key to consistent and compliant advice in the area?

Aiding advice?

Portafina managing director Jamie Smith-Thompson accepts the potential upsides of AI, such as increased efficiency, greater consistency of decisions, a higher output from a given number of staff, easier reporting and checking. However, he sees these as benefits only if costs are reduced and passed on to the client.

“A key limiting factor [of AI] is how you engage with the client to truly understand what it is they are trying to achieve and why – and to understand how they react when you discuss the possible consequences of their decisions,” he says.

“How does current AI pick up on the subtle nuances that tell you
that your client isn’t totally comfortable or entirely sure of themselves? How does it empathise with a client’s situation?”

Progeny Wealth director Alex Shaw says the more that can be done to ensure advice firms have a robust DB transfer process the better.

“I don’t see AI as replacing what we do; it is aiding what we do. We can have the AI data arrangements but still manage human interaction, how the client feels about it and what the family member wants to do. A lot of that can only be gleaned by asking questions over a few meetings. I’m not sure a computer is going to do that.”

Another IFA pulls DB transfers after FCA review

FinanFinance & Technology Research Centre director Ian McKenna highlights the progress IBM’s Watson system has made in the treatment of cancer as an example of the power of AI.

“Watson is already sophisticated enough to build a machine comparable with the most sophisticated financial adviser if it wanted to,” he says.

“That is not to say there isn’t a hugely important role for humans in advice, but we need to evolve and work with the technology. The application of AI to identify patterns and behaviour within advice firms has got huge potential. Imagine if the FCA had a version of Wealth Wizards’ system so that advice could either pass or fail?”

A compliance tool

McKenna says, going forward, there could be a system into which firms could drop every piece of advice to identify any potential inconsistencies, biases and risks, thereby reducing compliance risk.

“In the long term it should improve standards and outcomes, identify behavioural biases and ensure firms don’t apply biases in the recommendations they are giving.”

TCC group managing director, advisory services, Andy Sutherland points out there is often confusion between robotics – effectively automation without the application of judgement – and AI, underpinned by machine learning that has the capacity to develop a form of cognitive judgement through continual learning.g.

Robo firms signal their advice intentions

F the benefits of machine learning from a compliance perspective. Identifying DB transfer cases for review can be done in a fraction of the time using AI relative to humans following a paper trail.

“For example, where the customer objective for transferring their DB pension is accumulation – so no immediate need for taking an income – there is inherent risk that requires additional consideration. This includes looking at factors such as other sources of retirement income the client has got, the shape of their future income needs and their level of investment knowledge and experience.

“AI can tell you if all these factors are present, where they are and whether they are at the level expected. This has potential to save firms significant time and reduce costs,” says Sutherland.

“A further benefit is that when you are running AI over a population of files it can check them all, rather than just a small sample, at relatively immaterial additional cost.”

Sutherland says that once you can teach a machine to identify the most at-risk files, you can then devote your human resources more effectively and efficiently. However, he acknowledges the process needs to be right at the start. Indeed, the process is only as good as the information you put in.



The Big Interview: Ex-Skandia boss Peter Mann on why humans will beat artificial intelligence

Financial services veteran Peter Mann famously reserved a chair at board meetings to represent the client, his view being the only thing that really matters is whether they have been served. Although he winces at being described as client-centric, the ex-Skandia chief executive and Old Mutual Wealth vice chairman’s focus on the customer extends to […]

Sanlam fund managed solely by artificial intelligence

The fund will be the first in the world to be managed by AI and machine learning One of Sanlam Global Investment Solutions’ Ucits funds will now be solely managed through artificial intelligence. The Sanlam managed risk Ucits fund will be the first balanced fund in the world to be driven by AI and machine […]

Leading Edge – April 2017

There is little doubt 2017 will be a year of political uncertainty. Leading Edge is Royal London Asset Management’s regular review of investment markets. This edition explores some of the impacts that this uncertainty is having on investors, from the pitfalls of prediction within UK equity investing to the dangers of opting for convenience over […]


News and expert analysis straight to your inbox

Sign up


There are 3 comments at the moment, we would love to hear your opinion too.

  1. Will it be able to sign off as suitable and take the hit if deemed not to be after the event? Mmmmhhh

  2. I cannot see FOS accepting that a robot was to blame for bad advice, so the human element is always needed to interpret the findings and explain to the client.

    However, if AI was accepted as being of sufficient standard to meet FCA and FOS requirements, without recourse, then it could be a solution to the advice blockage that we have at the moment.

  3. It could work, but only if we as people are prepare to accept a computer making decisions, not us.

    I suspect most people the FCA included would have a hard time with that..

Leave a comment