The adoption of Artificial Intelligence based tools and techniques are helping business leaders indicatively transform industry verticals where repetitive decision making based on past-patterns is the key to success. Retailers like Sephora are leveraging AR and AI to help customers choose cosmetics; AI enabled supercomputers are helping alleviate Urban Traffic problems. A.I enabled systems are also beginning to supplement human traders in managing stock portfolios, and the result thus far has been mixed.
In a Harvard Business Review article, Megan Beck and Barry Libert explain “There are just a lot of things that machines can do better than human beings, and we shouldn’t be too proud to admit it. Many skilled jobs follow the same general workflow:
- Gather data
- Analyze the data
- Interpret the results
- Determine a recommended course of action
- Implement the course of action
We are beginning to see the increased adoption of machine-enabled investment management techniques including high speed trading, stock picking and portfolio re-balancing. Many of these activities are performed by skilled humans, traders trained in mathematical and analytical techniques who follow the steps highlighted above starting from Data Gathering to the implementation of a course of action.
Financial services industry following the buzzwords
The wealth-management industry that depends on innovative marketing techniques and been pushing ‘robo-advisor’ funds which seek to replace the traditional role of the financial advisor’s recommendations. Robo-advisors or Robo-advisers provide digital financial advice based on mathematical rules or algorithms. These algorithms are executed by software and thus financial advice do not require a human advisor. The software utilizes its algorithms to automatically allocate, manage and optimize clients’ assets.
Robo-advisors, that also conduct high-speed trading automatically are also fraught with risks. Some observers also highlight the risks associated with blindly adapting A.I techniques for high-speed pointing to incidents like the “2010 Flash Crash,” when high-frequency trading algorithms responsible for a 9 per cent drop and bounceback in the Dow Jones within just 36 minutes.
An article in Mother Jones highlight the risk of financial meltdown from computer algorithms that swap thousands of stocks each instant. (“Too Fast to Fail: How High-Speed Trading Fuels Wall Street Disasters“). A recent New York Times article summarizes A.I. Has Arrived in Investing. Humans Are Still Dominating.
“Large fund management companies like Fidelity and Vanguard say they use A.I. for a range of purposes, but they decline to be specific. BlackRock says it relies on it for heavy cognitive lifting, often by scouring data to tease out patterns that might remain obscure to human eyes and brains. Examples offered by Jessica Greaney, a company spokeswoman, include identifying and trying to exploit nonintuitive relationships between securities or market indicators, perusing social media “to gain insights on employee attitudes, sentiment and preferences,” and monitoring search engines for words being entered on particular topics, say cars or luxury goods.”
While there are challenges adoption of A.I and algorithms in trading, the techniques continue to gain popularity. Some experts believe that high-speed trading algorithms are responsible for more than half of trading in US stock markets. Computer programs automatically generate orders and cancel-orders trying to follow the trend minute-by-minute, trying to outmaneuver other high-speed trading systems.