Advice: a robo future?

Advice in Australia is expensive to provide.  So expensive, that people who need advice can’t afford it.  We have an advice gap and it’s only going to get worse as the baby boomers head into retirement.  But it’s not an insurmountable problem.

In our recent client strategy breakfast sessions, held in Melbourne and Sydney, we outlined three potential solutions to getting more advice to more people, at the right time and at the right cost.  Here we touch on the first one – algorithmic advice.

But first, a bit more on the advice gap.  There has been a tendency to assume that only people with substantial balances require advice, but in fact a much broader spectrum of the population would be well served by some sort of assistance, particularly as they head into retirement.  Retiring is complex – as a simple example, the majority of the working population between the ages of 56 and 65 should probably have a transition to retirement (TTR) strategy set up – but most of them don’t get advice and because it’s hard to set up a TTR without any help, so most of them go without.

Why is that?  For a lot of people, it’s the cost of advice.  Using fairly conservative estimates, the cost of providing an annual piece of high quality, compliant financial advice is $1,850 (including acquisition costs amortised over five years).  Historically this would have been more than covered by product revenues, but as today’s chart shows in a post-FOFA, post-Trowbridge environment, the ‘average’ super member retiring today (with a $150k balance and $500k in life insurance) generates product revenues of only $144 for the adviser, meaning an adviser service fee of 1.4% is required to provide a meagre ~$200 annual profit to the adviser.  1.4% customer fee – that sounds like a lot to us.


*upfront costs and expenses amortised over 5 years
So how do we deliver cost-effective advice to the average retiree?  One way is algorithmic advice (‘robo’ advice). The eminently scalable nature of technology means the marginal cost of a piece of algorithmic advice is startlingly low (one figure quoted by the panel at our strategy breakfast suggested $5 a pop).And so it’s interesting to look offshore to see who has been successful in providing algorithmic advice.  Frankly, the numbers are a bit underwhelming.  Betterment, one of the more well-known offers has raised $2.5b in five years (a third of netflows received by AMP’s North platform in the last twelve months alone).  Personal Capital has raised $1.5b over four years.  There is a long list of other providers with similar or lower figures attached to them.  The real action has been with Vanguard and Schwab, both late entrants but who have been gathering assets at pace (about $500m per month each since launch, as today’s second chart shows).

So what do Vanguard and Schwab have in common that the others don’t?  Well, it seems despite all the disruptors and incubators and fintech startups, brand, customer franchise and capability across the wealth value chain are all important to winning.What that means is that the traditional participants in wealth – banks and super funds – are actually very well positioned to be very successful as providers of algorithmic advice.  In fact, we’d go as far as to say as they are in pole position. Disruptors are great at getting new things going but much less good at scaling them up.

But there remains a stumbling block.  When we look at the global algorithmic advice offers, they are actually pretty narrow in proposition compared to the services a client receives through human face-to-face advice today.  If we break down the advice process into six steps, as we have done in the chart below, and look at where the technology providers are playing, it’s pretty well across the whole advice process except retirement strategy.  Now, that might be fine in a country without mandated superannuation savings (and where advice on how much to save, and what vehicle to put it in is a major part of the advice process), but where the savings level and vehicle is mandated, as it is in Australia, retirement strategy is core to advice, so algorithmic advice is going to be marginal until it can deal with retirement strategy.

Sample advice process

Of course, we’re only at version 0.1 of algorithmic advice.  The one certainty is that it will do more, and do it better.  And this, we are certain, will reduce the cost of advice and make it available to the average retiree.
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