In a recent study, 41 per cent of those surveyed said they believed obtaining financial advice would be a good way to use artificial intelligence. The research by Ericsson ConsumerLab further identified one-third would trust the fidelity of an AI interface more than a human for sensitive matters.
The study also highlighted that consumer adoption of new services has become greatly accelerated, with new propositions increasingly achieving mass-market use within just a few years. Organisations that choose to sit on the sidelines could lose considerable market share in a short period of time.
There will be many in our industry that will choose to rubbish such suggestions but there have always been those that have denied science: Galileo suffered with the same problem.
My increasing experience is that the deniers are, in reality, a small if highly vocal minority. Indeed, one adviser technology firm recently told me 90 per cent of current users it approached to participate in an automated advanced pilot responded positively. Clearly, people are looking to grow their businesses.
It may be an uncomfortable message to stomach but our industry has an image problem with a large number of consumers. Many of these will be individuals who struggle to afford or get good value from traditional advice. Surely automated propositions to fill this gap are a solution that suits everyone?
Recent research from Citizens Advice identifies 5.4 million people willing to pay for advice but not at current prices, and a further 14.5 million who want advice but are unable to afford it. By definition, these are not people who can be supported by traditional advice but they do represent an enormous opportunity for automated solutions.
Those looking to capitalise on this will need to find simple ways to communicate complex issues. At the FCA’s robo-advice event last September, one delegate talked of an automated advice process that needed 248 points of data entry by the user.
When you think about it, though, this is actually a relatively modest number of items compared with the extent of the data captured for a full holistic advice process.
Anyone who has spent any time looking at LV=’s Cora automated advice service will see data capture is a lengthy part of the process. Clearly, we are going to need to cultivate different ways of harvesting the information essential to give advice from consumers but that does not mean it cannot be done.
It is a rare week these days when I do not come across some new digital advice proposition being built for the UK market.
Looking at the, admittedly, limited information some of these services are making available, I will be interested to see how they meet the rules for assessing suitability, pension switching and self-defeating transactions. Rightly, there is no soft option for automated services.
A number of my colleagues are working on a project to map the full extent of factors necessary to deliver automated holistic financial advice involving accumulation and decumulation to meet the full UK regulation standard.
The magnitude of factors that need to be taken into account is daunting but it is nothing less than the challenge faced by human advisers.
It is crucial the FCA keeps a close eye on emerging new services to ensure they fully meet clearly documented and established regulatory requirements.
Although AI is in its early days, analysing large amounts of complex data, rationalising it and reaching conclusions complete with an audit trail and justification is exactly the sort of process to which it is ideally suited.
Increasing evidence of strong consumer demand for AI-based financial advice is not a threat to traditional advisers but an opportunity for the industry as a whole to serve a far wider section of the population.
Ian McKenna is director of the Finance & Technology Research Centre