By FINTECH Books Contributor, JB Beckett
For a fund analyst or wealth manager, fiduciary certainly goes well beyond selecting the cheapest passive fund for a client and leaving it there for 25 years. Can computers and robo-advisors become fiduciary?
Of course computers can be clever but have no inherent sense of self, humanity or fiduciary at creation. The first obstacle (or perhaps safeguard) is the absence of consciousness. The second is no morality. How then can robo-selectors put the client above all others? Perhaps through a fiduciary algorithm? Firstly robots follow 3 guiding laws: the Three Laws of Robotics (‘Asimov’s Laws’) that have come to be fundamental guiding principles for the robotics industry and could be applied to the fiduciary robo-adviser and robo-fund-selector.
Consider the game Go. In many ways the computations of a fund selector are far more complex than Go stratagem but the small judgemental biases are similar. Of course fund selection is neither science nor art, it combines fuzzy logic with data inputs and interactions. The other challenge is the retention of experience, digital wisdom if you will. Here AlphaGo solved through coupling self-learning with a differentiable neural computer (DNC). “The DNC architecture differs from recent neural memory frameworks, in that the memory can be selectively written to as well as read, allowing iterative modification of memory content according to its developers. The DNC then uses three distinct forms of differentiable attention. The first is content lookup, the second records transitions between consecutively written locations and the third allocates memory for writing.
Consider that digital does not need to better the human experience; simply deliver a comparable outcome that is devoid of illogical biases, consistent, reactive, impervious to influence and marketing to make objective decisions. If the very concept of fiduciary lies in a hierarchy of needs, rules and protocols, then these could potentially be digitalised in a New Fund Order.