The presence of artificial intelligence (AI) in today’s society is not only undeniable but also remarkably powerful. Whether we’re aware of it or not, many of us leverage AI on a daily basis.
Simply described, “artificial intelligence is the science of making computers do things that require intelligence when done by humans.” In other words, it’s pattern recognition.
A key role of AI is to transform large amounts of data into usable and meaningful information. Take, for example, Google Maps. One of the most commonly used apps in our smartphones analyzes the speed of traffic and suggests the fastest route to our next appointment. The use of complex programming and data analytics tools makes this available for use at the touch of a screen.
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Where does AI fit into banking, finance, and investing?
Digital transformation has caused significant changes in banking and finance. According to IT Business Edge, five of the most compelling reasons for the industry to adopt AI are:
- Compliance and fraud detection: AI can help reduce human error and analyze for suspicious transactions.
- Investment valuation: An algorithm, not just human discretion, can determine the best options based on fundamental and technical evidence.
- Reduced costs: Better efficiency and productivity of individual workers.
- Credit valuation and KYC: AI can perform automated checks.
- Customer service: Speedy, personalized service. You’ve likely already encountered this! Think, chatbots — those messenger bubbles that come up on websites (or even Facebook Messenger) that can guide you through your question or problem through a series of prompts.
Specifically, when it comes to investing, experts have attempted to predict market swings and benefit from them for decades. Granted, a very small number of investors have, in fact, been able to beat the stock market over the long run. Above all, the financial industry has been taking big steps to try and undertake this task through AI. And monitoring data is where the technology really shines when it comes to investing.
As Data Driven Investor explains, “what makes AI used for trade transactions different is that it can adapt when exposed to new 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.” In other words, you end up with is more informed investing decisions.
So far, the use of AI in investing and the stock market has been a fairly successful game changer.
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Artificial Intelligence’s current presence in the stock market
McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year to the global banking industry annually. In 2019, Nasdaq applied artificial intelligence on its U.S. stock market to detect irregular and potentially malicious trading activity.
Let’s take a look at some real-world examples of how AI-powered analysis and investing are currently being used.
Examples of AI-powered investing
AI in ETFs
In October of 2017, San Francisco-based firm EquBot launched the AI Powered Equity ETF, an exchange-traded fund that utilizes artificial intelligence in selecting its investments. Leveraging the power of IBM Watson, the ETF equals “a team of 1,000 research analysts, traders, and quants working around the clock.” It analyzes information about 6,000 U.S. listed securities by scanning daily through news articles, social media postings, and financial statements. The algorithm has the ability to select investments that suit the fund’s predetermined strategy.
AI in strategy and planning
Trade Ideas‘ “Holly” is an AI-powered self-learning robo-trading platform. Overnight, Holly, who has over a million stock scenarios stored, uses their AI engine to examine the market for that day of trading, manipulating its findings to offer tested long and short opportunities. Even more, Holly will only deliver strategies with a success rate of over 60% and a 2:1 Profit Factor on the next business day.
Holly also helps investors learn about lesser well-known stocks — hidden gems, instead of your typical corporate stocks like Apple or Netflix.
AI in client analysis
Sigmoidal, a New York-based consulting firm founded in 2016, develops AI and Robotic Process Automation (RPA) solutions for the investment management industry. In one case, the company used AI sentiment analysis to track investment signals for Baillie Gifford. Sigmoidal designed and developed a real-time AI-based tool to track and analyze clients’ sentiment across social media, towards companies from their portfolios.
Want to learn about other applications of AI in investing? Built In (an online start-up and tech community) has more real-world examples of companies using AI for smarter trading.
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AI in private equity
Research has shown that AI has “the potential to make a difference in private markets despite its struggles with highly transparent commodity and listed trading markets.”
As part of their AI Predictions 2021 series, PwC explains that private equity portfolio companies are actually ahead of the pack with AI – 31% (compared with 23% of companies that aren’t PE-backed) are AI leaders. They found that PE-backed firms’ top goals for AI initiatives in 2021 were:
- Operate more efficiently and/or increase productivity
- Innovation of products and services
- Revenue growth
- Better customer experiences
- Cost savings
- Improved internal decision-making
- Employee training and upskilling enhancements
- Reduce risk
- Talent retention and recruitment improvements
Some of the obstacles they’re facing? Developing AI models and data sets that can be used across the company, training employees on AI systems, making the AI systems responsible and trustworthy, and — quite crucially — measuring the ROI on AI.
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Can AI and financial professionals work together?
The stock market is one of the most complex fields to predict. Fluctuations in the stock market can happen. Unexpected election results, wars, natural disasters, government or corporate fraud, and missed earnings expectations all happen. And that’s just to name a few. Furthermore, some of the greatest lessons for humans? Whether pertaining to the stock market or life in general, they’ve been gained through hardships and experiences.
Based on the above examples, AI has made huge strides with stock selection, analysis, and investing. Most importantly, AI is not immediately going to replace advisors, managers, and analysts. It will, however, allow them to better manage market data. As the Equbot team explains:
“People will always need people to help guide them in reaching their financial goals, but for both investment managers and advisors, the application of AI-powered investing tools can be a powerful differentiator, time saver, and means of uncovering new and previously undiscovered opportunities to better serve clients and deliver meaningful value.”
Put even more succinctly, Mike Chen of PanAgora Asset Management explained for CNN, “It’s not man versus machine. It’s man plus machine.”
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The future of ArtificiaI Intelligence in wealth management
To sum up, AI advocates share plenty of excitement about the technology and its uses in the markets. Others maintain some degree of caution.
At this time, AI has shown its superiority in analyzing large amounts of data and identifying patterns. However, as mentioned above, it’s the soft skills, or ability to see past the raw data when evaluating investment opportunities, that separates the great investors from the rest.
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