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17th August 2017

Who’s to blame if a robo-adviser malfunctions?

Robo-advisers are a natural response to an age of sophisticated technology, fee compression, and regulation-mandated changes to IFA payment structures. But though these platforms aren’t new, and in fact have already entered the 2.0 phase of their existence, there are still a great many concerns to be overcome.

Customer’s not always right?

A central issue with robo-advice platforms is that the people who design and program them do not always sing from the same hymn sheet. Ask three different platforms for their automated insights, and it’s not impossible as an investor to be categorised as defensive by one, cautious by another and balanced by the third. This lack of uniformity is potentially a serious problem. The FCA has only recently warned IFAs on their suitability responsibilities and robo-advice platforms are subject to the same issues.

This problem may be compounded by the lack of human interaction with an adviser, often required to marry investor aspirations with financial reality. A robo service user, with no investment experience, may be tempted to engineer their answers in the suitability process to qualify for an ‘adventurous’ returns portfolio without understanding this increases portfolio volatility, and often means more severe loss-making periods during a market downturn. This is not a critical issue if the sum is part of a broader wealth plan or a diversified investment strategy, but in many cases, money invested in robo may be a crucial nest egg.

Algorithmic risk

Many of the new generation of robo-advisers operate according to their own proprietary algorithmic definitions of risk, when it comes to asset selection. This can lead to significant variation in the risk assigned to identical investments. An algorithmic assessment of recent historical data comparing the risk of gilts versus equites indicates there’s a closer risk parity, than a portfolio manager with the benefit of real world experience would suggest.

There is always the possibility that the systematic design and programming may not meet expectations. Whilst technology has significantly advanced, there are many examples of failure. Two decades ago, high profile funds reliant on systematic and algorithmic analysis built by the best and brightest minds, failed spectacularly. This was epitomised by the gargantuan fund Long Term Capital Management (LTCM). The theoretical brilliance of LTCM’s economics Nobel prize winning founders, provided virtually no protection to massive investor losses, which played a significant role in destabilising the entire global financial system.

It’s not as if algorithmic projections since the 1990s have displayed a hugely confidence building improvement. This was made plain (and inconvenient) again when the dotcom bubble burst, or more spectacularly in 2008 when the market lost trillions of dollars in value, which the overwhelming majority of systematic investment strategies typically did not protect client assets against. Goldman Sachs described the worst week of the 2008 crash as a series of daily “25 standard deviation events”. To make this jargon more digestible, this translates to the occurrence on consecutive days of market plummets that were modelled to happen once every 10,000 years!

Accordingly, systematic robo-advice platforms, whilst advanced and more technically robust, are at risk of assuming that humans will behave to form, and that ‘black swan’ events are far less likely than reality has demonstrated. The new algorithms are a recent enough phenomenon that there is no way of telling if they can weather new and extreme events. How does the investor know which robo to trust when none of them have an extended track record of successfully navigating through a variety of market conditions including crashes?

Market conditions

There is also the broader risks of the robo revolution to consider. So far capital investors have had a limited pool of new entrants to sink capital into. Nutmeg have received significant cash injections beyond initial expectation to help them sustain their customer acquisition strategies, and Moneyfarm just posted an operational loss of £6.4 million. The cost of client acquisition is getting higher not lower. But what happens as we see the second wave of robo platforms launch? How will the necessary capital investment be secured? Indeed, a recent FAMR report stated, “…there are approximately 100 ‘robo models’ either already launched or in development across a broad spectrum of services”. If the money flows into these new entrants instead, then the unsustainable expenditure of the leading robos becomes a bigger issue. 

Also, if investors leave a robo platform in significant enough quantities, once there is an inevitable serious downturn in the markets, and unproven systems make some painful losses, this could lead to a negative spiral. Robo providers shutting up shop could become a reality which would then leave consumers in the hands of the highest bidder. 

Digitised future

Robo-advice platforms will succeed as a major part of the solution to the financial advice gap left by RDR. There does however need to be in-depth analysis completed, beginning with a common standard for suitability. Advisers should not simply outsource advice to technology, but instead choose platforms that can effectively approximate their customers’ preferences and the guidance that they would usually offer. Alternatively, there is a strong case for a ‘non-advised’ digital portfolio service, managed by a proven battle hardened human team rather than a machine. This alternative offers the IFA many of the same benefits of providing robo advice (i.e. the ability to service a previously dormant back book at a low cost) but mitigates many of the risks laid out above. In this model, introduction rather than advice is given and the investor then takes entire responsibility for selecting an appropriate portfolio based on its basic characteristics. This could enable the IFA to offer a service to clients that became uneconomic post RDR. Either way, dormant back books combined with new generations of investors will equate to an enormous market opportunity. Add a failed robo provider or two into the mix, and the market may really open up.

Lester Petch is CEO of non-advised white label FinchTech

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