Artificial intelligence in the form of robots has caused most of the job losses in manufacturing in the U.S. over the past decade, according to experts, and it's possible the investment management industry could be next to feel AI's impact on employment.
The more than 142,000 chartered financial analysts around the world practicing as analysts or portfolio managers might be the first to feel the impact, judging by the recent moves of BlackRock (BLK) Inc. (BLK) to base more of its equity strategies on quantitative computer models. The switch is likely to cost around 40 BlackRock employees, including portfolio managers, their jobs. BlackRock is unlikely to be alone for long.
As part of the switch, BlackRock will reduce the fees on some of its active funds in an effort to improve their competitiveness with low-cost index funds and exchange-traded funds.
Many other large investment management firms no doubt will step up their data mining efforts, as BlackRock is doing, so they can remain competitive with the world's largest manager of institutional assets.
To protect their jobs, analysts and portfolio managers must embrace the new artificial intelligence and machine learning tools and use them to improve their own utility. Those who find new ways to use the power of the data mining techniques these tools make possible will survive in this new high-tech world.
The investment management industry embraced computers early, with the advent of computerized spreadsheets such as VisiCalc and Lotus 123. These greatly increased the amount of data analysts could process, improved the accuracy of their forecasts and allowed them to expand the reach of their research efforts to more stocks.
Modern communications systems, including satellite and digital systems, combined with that computing power, allowed money management firms to research and invest in stocks outside the U.S. as easily as in the U.S.
The more intense analysis of stocks in turn, no doubt, increased the efficiency of the stock markets and made it more difficult to generate alpha.
Computers also made index funds more viable and the low costs of these vehicles increased the pressure on active managers to produce alpha to justify their fees.
Data mining has wrought significant changes in intelligence gathering, in marketing, in deep space exploration. It will bring about significant changes in the investment management industry and even in the stock markets, the scope of which can't be fully foreseen at present.
One likely result of more intensive data mining using the increased power of computers and models is that the equity markets will become even more efficient than they are, making the capture of alpha even more difficult.
Active managers, including BlackRock, already have seen significant withdrawals of funds as institutions and individuals, disappointed with the returns from their active portfolios, switched to indexing. If the active managers can't improve their returns in coming years there will be slim pickings for those managers as more and more clients index larger and larger parts of their assets. In that case, there will be fewer jobs for portfolio managers and security analysts.
Besides shifting more assets to index funds, clients are moving more into alternative investments, such as real estate and oil and gas, though even here data mining might make the markets more efficient.
Quantitative approaches to investing in the stock and bond markets have been around for almost 40 years, but new technologies are bringing them to new levels. Money management firms and the people who work in them had best be prepared to adapt to the new world of artificial intelligence and machine learning or be prepared to become extinct.
This article originally appeared in the April 17, 2017 print issue as, "AI? It's not sci-fi anymore".