Financial services companies, including technology oriented (fintech) start-ups, are emerging to challenge the roles of banks and the large financial institutions. Fintechs are rapidly transforming and disrupting the marketplace by providing digital or ‘robo-advice’ using highly sophisticated algorithms operating on mobile and web-based environments.
Last month, the Minister for Revenue and Financial Services, Kelly O’Dwyer, announced the Turnbull Government’s intention to introduce professional standards legislation to set higher competence and ethical standards for human financial advisers – a move that is already under pressure from the robo environment.
While the financial advice sector has expanded and matured over the past two decades, fuelled in part by new technologies, the regulatory framework has taken time to catch up. However, the rapid pace of ICT development – with A.T. Kearney predicting robo-advisers in the US will manage investment assets worth $2 trillion by 2020 – makes it critical that we plan for a world where technology is in the driver’s seat.
Indeed, Sam Sicilia, the chief investment officer of industry superannuation fund Hostplus has even suggested that Artificial Intelligence (AI) will make human financial advisers redundant within the next 10 years. Policy decisions might influence that outcome, but as learning machines become smarter, their ability to undertake a wider range of functions will only increase.
Where is the dividing line between human financial advisers and robo-advisers?
In March this year, ASIC canvassed the financial services industry on how robo-advisers should be regulated, consulting with stakeholders about the practicality of requiring expertise to explain the scope, design, rules and risks behind the algorithms used to provide financial advice.
Then in August, ASIC laid down guidelines for monitoring and testing algorithms. The regulatory guidance also requires businesses carrying out robo-advice to have people within the business who understand the ‘rationale, risk and rules’ used by the algorithms and have the skills to review the resulting robo-advice.
The ASIC position does not go as far as the one adopted by the EU, which provides an explicit ‘right to explain’ and ‘right to challenge’ on decisions made by algorithms. Nor does the ASIC guidance place an explicit onus on the algorithmic provider to explain, in simple terms, the logic behind an algorithmic decision. This might be intentional since algorithms may involve highly complex code and technical considerations well beyond the skillset expected from an average financial services adviser.
In addition, the logic behind an algorithm can include confidential trade secrets and other legal concerns, with a forced disclosure potentially risking a fintech start-up’s competitive advantage and trade secrets.
The US Securities and Exchange Commission (SEC) is currently exploring how to regulate robo-advisers with Commissioner Kara M. Stein asking, “Who is responsible when algorithms go awry? …In a world where programming errors are just as damaging to investors as improper sales practices, our regulatory approach may need to evolve.”
In a recent public address, she said, “In our capital markets, we have in many ways already gone the way of the robotic, driverless car, without having a robust discussion of how we should regulate it. Estimates for total market volume attributable to algorithmic trading routinely exceed 50 per cent. We are not in the testing phase.”
Her concerns were picked up this month by the Australian Productivity Commission in its draft Data Availability and Use report, which recommends that consumers should have a right to appeal automated decisions.
In his ground-breaking book, “The Second Machine Age”, MIT scientist and futurist Andrew McAfee highlights the limitations of relying too heavily on algorithms, writing: “Ideation, creativity, and innovation are often described as 'thinking outside the box', and this characterisation indicates another large and reasonably sustainable advantage of human over digital labor. Computers and robots remain lousy at doing anything outside the frame of their programming.
However, with the rapid advances in AI and machine learning, that could change.
Who said a machine would not be able to beat humans at chess?
Mr McAfee will discuss this issue further when he presents the keynote at the ACS Reimagination Thought Leaders Summit in Sydney on Wednesday.
Anthony Wong is President of the ACS and Chief Executive of AGW Consulting P/L, a multidisciplinary ICT, Intellectual Property Legal and Consulting Practice.