The rise of automated advice and new technology is changing the face of financial planning. It is offering low-cost advice to investors who previously couldn’t afford it and bolstering the advice of traditional planners with powerful new analytical tools.
However, there’s a problem.
Many automated advice providers are simply replicating the increasingly outdated traditional advice process, which places an investor’s risk tolerance at its apex and delivers product-led solutions.
This approach, which came from reams of legislation aimed at protecting consumers over the past 15 years, delivered advice which was superficially compliant. But it was advice which all too often led to a product which had little bearing on an investor’s actual goals.
Many automated advice providers are now falling into the same trap. They may offer lower-cost advice but their fees are still tied to an investment (often an exchange-traded fund portfolio) rather than the advice they are delivering.
New digital risks
The quality of digital advice needs to match that provided by traditional financial planning dealer groups to “ensure consumer and stakeholder trust and confidence,” according to the Financial Ombudsman Service’s (FOS) annual report.
FOS reviewed 1,141 investment and advice disputes in 2015-16–inappropriate advice was the largest category, accounting for 28% of cases.
Financial planners accounted for the largest source of complaints (55%) and managed investment disputes were the largest category (37%), with many investors complaining that the advice they received wasn’t suitable for their goals, objectives or risk tolerance, or that risks were not adequately disclosed or explained.
These risks are arguably exacerbated when using automated advice tools which rely on digital communication channels to explain complex financial topics. In fact, FOS rates those risks so highly that it believes the government should introduce a new compensation scheme to protect consumers.
“We consider that the growth of digital advice in Australia increases the need to establish a compensation scheme of last resort,” according to FOS.
Algorithms and technology represent the key risks with a recent survey of CFA Institute global members rating flaws in algorithms as the biggest risk faced by robo-advisors.
Building better digital advice tools
The Australian Securities and Investments Commission (ASIC) has recognised the importance of technology and is placing stringent requirements on robo-advisors to monitor and test advice-based algorithms.
This includes: maintaining documentation setting out the purpose, scope and design of algorithms; regular testing of algorithms which is documented; timely algorithm updates to reflect new market or legal requirements; ongoing reviews of advice quality; controls and processes to suspend advice if an algorithm error is detected; and processes and security arrangements for managing any algorithm changes (and keeping those records for seven years).
These obligations will only become more burdensome as the fledgling robo-advice industry begins to incorporate a more complex, goals-based advice process into their businesses. This approach is necessarily more complicated but has the potential to actually deliver the outcome that investors want.
The shift to goals-based advice by robo-advisors is likely to follow a similar path as traditional advice (it will use much of the same underlying technology).
Risk profiling still plays a key role but investor goals are placed at the apex of the process as AMP recently did by overhauling its traditional advice with the launch of AMP Advice.
A more nuanced approach to risk profiling will move well beyond simple questionnaires which assess risk tolerance (an investor’s willingness to take on risk) to include different components such as risk aversion (the flip side of risk tolerance), risk capacity (the financial ability to endure losses) and risk need (the amount of risk needed to likely achieve goals).
Behavioural finance concepts will also become more deeply ingrained into the advice process and more accurately reveal the future behaviour (or risk-return trade-offs) that investors are most likely to make under different circumstances.
Goals-based advice remains complex territory and taking a best-of-breed approach to its many facets can help firms implement successful solutions faster while lowering their risks.
So far, many robo-advisors have competed on a lower cost of advice when they instead should be focused on raising the quality of their advice.
Automated advice–and similar technology used by face-to-face advisers–has the potential to deliver better results for investors, but only if we learn from the mistakes of the past.