It is undeniable that Artificial Intelligence is here and that it is poised to change the way we perceive, interact and organize our world. Indeed, the future has arrived.
But how did we get here? The evolution of has not been an overnight epiphany. In fact, it is now going on six decades since the Dartmouth Conferences in the summer of 1956 when a small group of computer scientists dared to dream of a world in which machines could sense, reason and think just like humans.
For years, development came in fits and starts but since 2012, the world has witnessed exponential breakthroughs in the field. The feats that have now been achieved only fall into a subset referred to as Narrow AI in the sense that AI solutions are only capable of performing specific tasks as well as, and in an increasing number of cases better than humans. However, Narrow AI might be seen as an unfitting term when one considers that those specific applications are myriad in number and capable of an astounding amount of customization in their execution.
Transformative force across industries
In a sense, AI is set to transform all facets of life ranging from heavy industry to medicine, transportation, commerce, art, communication and of course, finance. Already, we are witnessing its application in algorithmic trading, underwriting, personal finance, market analysis and data mining and portfolio management. In recent years, advances in AI and increases in processing power and the sizes of available data sets have placed these intelligent tools and algorithms in the hands of a wider class of investors.
As a result, everyday investors are coming up with smarter, less risky, trading strategies.
For many first-time investors, “rational” is a descriptor that is rarely used to describe investment portfolios. But for two MBA students at UC-Berkeley, that was the exact word used to describe investment decisions made by an artificially intelligent platform they created.
Game-changing ETFs
Late last year, through their company, Equbot, Art Amador and Chida Khatua launched an AI-powered exchange-traded fund the first of its kind. Powered by IBM’s Watson platform, this ETF uses machine learning algorithms to analyze millions of data points, helping to build the perfect portfolio with up to 70 stocks.
AI-powered ETFs are among a growing number of investment platforms that are using supervised learning, unsupervised learning (both offshoots of machine learning), and deep learning to help investors make profitable investment decisions.
Quantitative hedge funds are increasingly adopting yet another approach in which AI is deployed in the development of complex mathematical models to develop astute investment strategies derived from the analysis of immense amounts of data.
The use of intelligent algorithms to make stock picks isn’t new. Frequency traders, hedge funds, and other institutional investors have been using them for decades, though they weren’t quite as effective as they’ve become lately.
Art and Chida are quick to point out that what sets their approach apart from those conventionally applied by other players in the financial market arena is that Equbot’s solution is designed to make rational decisions that can comprehensively be traced back and understood by humans.
This reigned-in application has its advantages, chief among which is the capacity to teach the novice investor the subtleties of strategy. However, if one takes a leap of faith and untethers the machine as some of the biggest hedge funds such as Man Group, it makes decisions which puzzle its human creators, seeming irrational yet profitable.
What then, do those new changes mean for those who do the jobs that appear to be increasingly becoming the domain of the intelligent machine?
AI-driven tools have already been shown to be capable of analyzing tens of orders of magnitude more information that humans and making hundreds of investment decisions in a fraction of the time it takes a small army of financial analysts or asset managers to perform similar tasks.
Industry leaders such as the Chief Investment Officer of Japan’s Government Pension Investment Fund will tell you that AI is set to replace asset managers in short-term trading. Those asset managers will either move to long-term trading, which requires more intuition and client engagement or learn to code and contribute to the growing trend. Those who do not will have to be laid off and firms that now staff hundreds and require high volume email management services just to keep internal communications sane will have to restructure or get trampled as everyone else marches forward.
For the investor, it will mean more accurate strategies and informed decision-making as well as a reduction in fees.
