That is a New Fund Order, Artificial Intelligence (AI) looms over all of us like a kaiju*, a giant 200-foot Godzilla. Bluntly put, finance needs to find new solutions through technology or become obsolete by it.

Finance needs to find new solutions through technology or become obsoleted by it.

Today the looming threat of AI seems so obvious and very real. Why then did finance so badly underestimate the threat for twenty years? Using my observations, it was why I was motivated in 2015 to write #NewFundOrder, where technology meets finance meet's philosophy, meets science fiction.

Companies like Google (Alphabet), Microsoft, Facebook were not only changing finance externally but also becoming the largest capitalised stocks within it, creating a huge feedback and validation of technology as both a source of economic growth and social advancement. CitiGroup believed RoboAdvisors will hit $5 trillion AUM in the next decade. A more recent study by Deloitte estimated that “assets under automated management” (including hybrid offerings) in the U.S. will grow to USD7 trillion by the year 2025 from about USD300 billion today.

Karl Marx wrote “the more the division of labour and application of machinery extend, the more does competition extend among the worker”.  

Until the late 1970s, hundreds of clerks updated futures prices on chalkboards and recorded them on Polaroid film. Thousands of traders walked the pits, hundreds of thousands of accountants, actuaries, typing pools, administrators and computers processed, calculated, deliberated and predicted…all gone!

My own profession is not immune to this threat. The fund selection community is quickly waking up to the threat and something we are actively discussing at the Association of Professional Investors (APFI), headed up in South Africa by Riad Daniels at GT Capital. After all, if fund managers cannot add value, then what value do the people who select them offer? Obvious symptoms of this shift include the large shift towards index investing and Exchange Traded Funds (ETFs). Performance and quant-based analysis are rapidly becoming codified and automated. Meanwhile, traditional qualitative fund analysis, itself judgemental based, is seeing disruption from crowd research platforms like SharingAlpha.

So, if the value of human intelligence is left in question, what then for artificial intelligence? It certainly offers advantages both in the rapid assimilation of big data, learning from changes in data and predictive modelling. A simple model was already proposed by Ludwig and Pivioso in their 2005 machine-learning paper. They also considered what sort of algorithm should a fund selection robo adopt from three choices: decision-tree, neural network or a naive Bayes approach. Ludwig and Pivioso concluded that all three approaches outperformed simple scoring models typically employed by human fund selectors. What is frightening was that this was achieved with only a simple array of data inputs.

Now consider the technology advancement and complexity of data available 13 years on since that paper. AI can now begin to replicate judgemental nudges and biases based on common material changes like price, attribution data, manager experience, tenure, benchmark, fund changes, moving firm, news flow and so on. I began to imagine if fund selection can be derived from AI: especially so when we consider key advances in Differentiable Neural Computing (DNC). DNC can literally read and rewrite memory, it becomes iterative, wise even. It was used to enable AlphaGo to beat the best Go player in the world across 250 to the power 150 possible moves.

Could the human condition still infect AI? Yes, but AI can follow the Three Laws of Robotics by the science fiction author Isaac Asimov.

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey the orders given to it by human beings except where such orders would conflict with the First Law.
3. A robot must protect its own existence so long as such protection does not conflict with the First or Second Laws.

Taking these laws, it is not unfathomable that computers can be programmed to put the interest of the client first and foremost. AI can even offer the Robo Fund Selector a framework to set ESG criteria and identify better solutions to improve ethical and sustainable investing.

Thus, the New Fund Order, an unrelenting digitalisation of asset management. How then to survive the kaiju, how to survive digital death?

Be prepared, my lecture on AI Robo Fund Selection is available at FintechCircle Institute.

If this sounds all too monstrous then you’re probably right. Godzilla approaches.

*Film Godzilla, (1954) Ishirō Honda.