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Robo advice: the good, bad and the ugly

    CPD
    Approx.30min

    In this way, rather than a standalone product, robo-advice can actually compliment a full advice model and help attract customers for the long-term.

    A word of caution is required at this stage on the perceived scale of the advice gap itself and just how big an opportunity this actually creates for automated services.

    It is true that robo-advice has real potential to appeal to those who can no longer afford face-to-face advice but there is a tendency among robo-advice developers to portray the number of potential customers who have fallen into this gap as being somehow limitless.

    The most realistic figures come from Citizens Advice and Deloitte which have both estimated that the number of people who have fallen into the advice gap stands at 5.4m or 5.5m, respectively. However, it should not be assumed that just because someone has previously received advice in the past, they will necessarily need or want it now.

    The biggest – and very real - danger then for robo-advice is that it is essentially a product in search of a market where the value pool could be significantly smaller than many perceive it to be. Robos may be plotting a takeover of financial services but any rapid rise in the technology could therefore quickly lead to oversupply in the market.

    Glitches in the system?

    Establishing a robo-advice offering does not come without its challenges. For now at least, the technology certainly appears to have its limitations. The need for many investors to eventually move from automated to full advice, for instance, highlights the current inability of robo-advice to deal with complexity and evolve with an investors’ financial needs as they change over time.

    Currently, robo-advice can only really cater for an individual whose financial circumstances fit with one of several predetermined categories that are calculated using algorithms. This may be right for someone beginning to save for retirement, as their financial needs can largely be assessed through risk profiling.

    By contrast, the circumstances and choice available to someone in later life cannot be so easily determined. To give just one example, robo-advisers cannot offer the personalised tax advice that a face-to-face adviser can provide, something which is likely to be particularly important for those looking to navigate the complex tax arrangements around pensions.

    Then there is of course the point that a robo can only ever be as good as the data it receives. If the wrong data is fed into an inappropriate algorithm, then this will inevitably result in the wrong recommendation.

    The US is currently working on ways to develop robo-advice so that it is sophisticated enough to deal with a wider variety of financial circumstances and different degrees of complexity, known by the industry as ‘robo-advice 2.0’.