Robots in the financial world, specifically in the area of investments and savings is one the fastest growing and interesting areas right now. For a variety of reasons, it holds a lot of promise for both consumers and businesses.
As it happened, I read this article about robo-advisory the other day. Unfortunately for me, who read it, it was the most misinformed string of words I have ever read. Even though I’m no expert on robo-advisory, I could tell that the author of this piece was even further down the ladder of ignorance than I am.
Judging by this article, there seems to be a lot of confusion on exactly what robots in the financial context are, and what they can do for us. The impact of misinforming the public in such an important area can be arduous task to reset. If they – the journalists who are supposed to inform us, get it wrong, ideas form and we are stuck with those ideas for a long time.
What do we mean by robo-advice?
Anyone who can find a way to put “Robot” in to the naming of a category or product is a genius. Robots is the word-du-jour and the Insta-cool for anything. But in its most common form robo-advice sounds much cooler than it actually is.
The basic application, and what we generally mean when talk about robo-advice, is a digital, online automation to document what your savings preferences are in terms of risk, savings horizon, and current savings, and then invest in (low cost) long term portfolios of ETF:s and/or mutual funds that matches your preferences. A part of the smartness is that the portfolios are automatically rebalanced to keep your asset allocation intact. Some of them also have automated stop-loss functionality and ways to avoid trading in extreme market conditions. It’s supposed to be a long term, worry-free way to invest your funds.
Then there is a range from the more basic applications to the advanced. The more advanced will offer more opportunities to customize, and also offer a wider variety of strategies and possible choice of securities. They will also evaluate and rebalance your portfolios continuously to adapt to current market sentiment and volatility.
In US, where this has practice has come the furthest; Vanguard, Schwab, Wealthfront and Betterment are the biggest players categorized as robo-advisors. They all differ a little bit from each other, and the variations can be found in fee-structure, level of access to personal help and sophistication in terms of smart functionality as tax-loss-harvesting (förlustavdrag in Swedish). Some of these platforms have a minimum required account size of $0 – up to $5000, and trade commissions ranging from 0% and up.
The Swedish players
The Swedish market in this field is populated with beta, and newly launched players. I have no exact figure on how many new companies have been started in this field but there has been quite a lot of activity during the past couple of years.
The Swedish players I found certainly look the part, but have yet to prove their potential. The market seems to be a bit crowded and undifferentiated at the moment. Almost all of them seems to be targeting a younger audience, which might be a clever move even though you could argue that the interest for investing in your twenties is about as low as it gets.
One company, Lifeplan, have been around for a while, and have had a smart way of getting to market. They started out in the area of occupational pensions, and have been growing in that area for quite some time, perfecting algorithms, business plan and so on. Now they are starting to move into privately arranged pensions.
I suspect the smaller players have difficulty with getting traction on the market, and bringing a critical mass of customers through the door. As most newcomers they have a trust issue, as well as scale-issue.
The large banks have yet to launch any viable products in this segment, but they could rather easily execute and launch robo-advice and within six months have the scale to make this a real business, albeit with the caveat that it might cannibalise traditional advisory services – or, what’s left of it. Or as a guy from megabank JP Morgan pre-eminently said, referring to fintech startups:
“They have the innovation – we have the scale. Scale always beats innovation”
All players (not just the local players) with small variations draw on three major things in its market positioning and marketing.
A common denominator is that they rely on science instead of (human) analysis of the markets and securities. By basically eliminating the human factor in all steps – including the emotional instinct to sell everything when the markets are plummeting – they can display better long term results. The quality and the significant and commercial differences in each company’s algorithms become increasingly important – and at the same time – the quality of the advisor, i.e. – the analyst and the broker becomes reduced in importance.
They also emphasize low cost to create a better yield over the long term, rather than high cost portfolios and the potential for beating the market. Of course, this is one of the most debated issues the financial industry, if you can in fact over the long term, beat the market.
Not all players tout independence as one of the top three unique selling propositions, but for some, especially the smaller players this seems to be an important argument. MiFiD II might in part change the dynamic of this argument, since provisions in the value chain becomes prohibited.
The financial landscape is enormous and artificial intelligence is going to change it dramatically. It’s just a matter of time. When they talk about robots taking the jobs of bankers. To a large degree, they talk about banks.
But still, robo-advice is a small part of that financial universe. A global estimation of assets under management for 2015 was around $70 trillion (that’s $70,000,000,000,000!!) and the part of that managed by so called robo-advisors was counted in the lower billions. The three largest players are Vanguard Personal Advisor Services ($41 billion in assets under management), Schwab Intelligent Portfolios ($8.2 billion in assets under management), and Wealthfront, ($3.5 billion in AUM).
Consulting firm A.T Kearney has predicted that the total managed assets for robo-advisors will be around $2.2 trillion by the year 2020. That’s not very impressive compared to a ballpark figure of $70 trillion for the traditional asset managers.
Estimated AUM for robo-advising
For consumers and investors, this new breed of investment vehicles could have a lot of positive effects.
- The large group of under advised that now can get proper counselling without paying high fees, and as a result can make sound investments and grow their economy.
- People in general hold to much cash. In a low, or negative interest rate environment, holding cash means loosing capital. This means there are plenty of opportunities for simple, low threshold applications to reach out to investors.
- People live longer these days, and the importance of planning for retirement has never been greater, so obviously, putting these tools in the hands of many is a great contribution to society – and at the same time, it makes great business sense.
- It’s also a customer centric solution – it’s fun and easy and cheap, and for the benefit of the banks it’s cost efficient and can be distributed at scale, and it’ll make you “instantly” MIFID II-compliant.
- For large banks, automated advisory can have many functions. It can be a way to capture a larger portion of the market, i.e. – advising the under advised with a simple and intuitive tool, and at the same time offering more advanced services for mass affluent and the rich – to super rich.
- It could also, quite possibly act as an onboarding tool or gateway in to the banks ecosystem. The process of advising yourself via a digital tool, doing the KYC-process gets you up to speed and in the system.
Nowadays, it’s all about the algorithm
Digital advisors differ in one significant way from each other. The algorithms vary in terms of sophistication. From the very simple (maybe even bought of the shelf) that is based on a number of tick-boxes creates a single portfolio to more complex structures that creates multiple portfolios and that constantly reviews a huge number of instruments and scenarios in order to construct an portfolio based on current holdings, investment horizon, and risk tolerance.
In the good old days you trusted your banker and you had a great deal of respect for the knowledge of the analysts and traders. They were (and are to some extent still are) revered and idolized for the way they could single out and pick the winners from the losers. Themselves becoming rich in the process added to their glow.
I suspect that this is all going away. The analyst and traders are no longer the ones running the show on the trading floor. They are still there (albeit to a lesser extent) but it’s the algorithms that do the heavy lifting.
Trust in the algorithm
The big story here is not how different algorithms differ, or how they handle different market situations. Just as with any other big change, it’s about adoption to a new idea, and at scale believing that the new is by far better than the old.
I believe we are moving towards a situation where trust in humans is becoming a suspicious stance, just like owning a gas driven car is starting to look and feel antiquated.
People are volatile; they make frequent mistakes and are guided by unclear and sometimes conflicting goals. In a pre-MiFID-world, the analyst feeling of the market sentiment was enough to give advice. Would anyone take that bet today? You could see a scenario today where you put a certain type of trust in an institution to deposit your cash – and another type of trust to have the best programmers and algorithms to invest them safely, cheaply and profitably. The institutional banks can combine those and have it all.
It’s natural really – we put more and more trust in algorithms, and more and more of our lives are controlled by them. In the investment world, the better they perform the better I’m off.
Usually what is needed for real customer adoption, is technical development that goes hand in hand with human behavior, adoption and the benefit of real tangible value in comparison with the old. When we change, when we shift our trust in other humans to handle our funds, to algorithms, things will really start to accelerate.