Have you considered diversifying your investment portfolio?
Of course you have.
Have you considered diversifying the tools you use for investing?
Maybe not.
This is exactly what financial management firms are beginning to do. Industry-wide changes are happening right now in global finance, and artificial intelligence (AI) is at the forefront of those changes.
By utilizing AI capable of machine learning, the way we invest is drastically changing. Algorithms are becoming the core decision makers for companies processing multibillion-dollar transactions.
And it’s working.
What Led to the Rise of AI?
For years now, program code has been a tool for financial trade, so using computers to aid us in investment strategy is certainly nothing new. What makes AI used for trade transactions different is that it can adapt when exposed to new data.
Recently there has been a push to work with AI in the investment industry. The conditions to do so are optimal now, or at least more so than in the past.
Huge leaps have been made in computer processing abilities, allowing the cost of quality processing tech to decrease. There has also been a sharp increase in the availability of accessible data, which AI can use as needed.
In addition, the cost of storing that data has declined significantly1. So while using AI for investment guidance and data analysis has always been a great opportunity, it simply was not cost effective enough to become a business model until recently.
What Can AI Bring to the Table?
AI is an ideal tool for monitoring data. Whether that’s data you do not have the time to monitor or data you may not have considered to be impactful to your stocks. AI sees those relationships that most people cannot see.
Think about how much more informed investment decisions are with AI. It can provide up-to-date information on product movement throughout the supply chain, analysis of weather forecasts and outline search engine topics, then use this information to determine a profitable investing strategy2.
This technology is capable of analyzing reports and press releases for words which point to a stock taking off or falling flat. AI capable of machine learning is also being used to predict overall market sentiments. All these tools combined allow AI to accurately suss out the most efficient way to complete a trade.
Investment firms are not the only ones who can benefit from AI; any business in need of liquidity risk management will benefit too. An intelligent machine trained to monitor company finances ensures that if you take a hit financially, you will have an appropriate amount of collateral to absorb losses without putting your shareholders at risk3.
Hedge Fund Investing
Nearly 90 percent of hedge fund trades are currently conducted by computers that have been hard coded by technicians4. These coded computers are not like AI though, as they are incapable of deep learning. Companies like Man AHL are moving away from hard-coded programming and towards AI.
Man AHL specializes in quantitative trading, which is a branch of hedge fund investing that relies on computers and algorithms when trading client assets. They boast the most comprehensive solutions in trade finance and services. Although that may sound like a marketing tagline, they are indeed leading the way with their foray into AI.
In a case study reviewing the intelligent machines used by Man AHL, it was found that their AI could allocate trade tasks to specific algorithms or for human execution much more efficiently than when this allocation process was conducted manually. It saved time and money.
Normally this allocation would be conducted by human workers, but it is incredibly difficult for people to hash out which trade task best aligns with which algorithm or which human specialist5. This is due to all the noise present in transaction data. It’s not easy to see the difference between quality information and noise, but AI can.
Though the use of AI was approached with great caution at the beginning, by 2015, Man AHL was receiving about half of its profits via AI-led methods. This was in spite of AI having control of just a limited subset of the AHL assets. Since then, AHL’s fund assets have increased more than fivefold. You could say that things have worked out.
Managing Global Trade Portfolios
Citi Treasury and Trade Solutions has begun to use AI to review the over 9 million global trades they process annually. Traditionally, this is a time-consuming process that is tedious in nature. The person conducting the reviews must also monitor regulatory compliance of the trade transactions; there is plenty of room for fatigue and mistakes.
Citi uses AI that is capable of researching and comparing data collected from both previous and present transactions. This helps provides context and easily-understood data to the person carrying out the trade transaction reviews. The amount of manual research that had previously been the standard within the industry has been significantly reduced by the assistance of AI.
AI is also part of educating clients who use Citi’s services. When it comes to advising individual investors, the Citi recommendation engine can offer guidance and create customized research documents to inform any next steps. Notifications about important developments within the investor’s portfolio are sent out to keep them in the loop.
Humans and AI Make the Best Team
“It’s not man versus machine. It’s man plus machine.”- Mike Chen
It’s not that AI is all around better than humans, it’s just that we excel at different tasks. AI can multitask at a level that our brains don’t have the ability to; it can gather data immeasurably faster.
However, data scientists and engineers are still needed to build the AI infrastructure. After they have set the parameters for the AI’s system, the machine has the ability to change through deep learning.
In his interview with CNN last February, Mike Chen of PanAgora Asset Management clarified, “It’s not man versus machine. It’s man plus machine.” You can see this in the way that AI relies on humans to provide rules and to create the data it draws upon. It is currently a supplementary tool to be used alongside the human knowledge of investing.
Working with AI
AI can save time. It can save money. And in the situations where it doesn’t, then you probably shouldn’t be using AI. It is unlikely you’ll find yourself in such a situation though, as the future of AI in trade looks more than promising.
Deep learning is the reason AI stands out. This ability to learn means an intelligent machine can manage your risks as an investor by surveying the path ahead for burgeoning opportunities or looming threats, allowing you to respond quickly.
Or better yet, an intelligent machine can respond for you while you spend your time doing other high-demand tasks.
Corporations and individuals alike must ask themselves what is most efficient: an algorithm or a human? Most of the time, it’s a combination of both.
References
- Satariano, A. & Kumar, N. (2017, Sept. 26). The Massive Hedge Fund Betting on AI. Retrieved from: https://www.bloomberg.com/news/features/2017-09-27/the-massive-hedge-fund-betting-on-ai
- Dannemiller, D. & Halpin, L. (2019). Artificial intelligence. The next frontier for investment management firms. Retrieved from:https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Financial-Services/fsi-artificial-intelligence-investment-mgmt.pdf
- The Editors of the Federal Reserve Website. (2017, Oct. 23). Liquidity Risk Management. Federal Reserve. Retrieved from: https://www.federalreserve.gov/supervisionreg/topics/liquidity_risk.htm
- Chang, M. (2018, Oct.4). How A.I. Traders Will Dominate Hedge Fund Industry [https://youtu.be/lzaBbQKUtAA]. Retrieved from: https://www.youtube.com/watch?v=lzaBbQKUtAA
- Cao, L. (2019). AI Pioneers in Investment Management. CFA Institute. Retrieved from:https://www.cfainstitute.org/-/media/documents/survey/AI-Pioneers-in-Investment-Management.ashx
