AI: The Best New Technology in the Investor’s Toolkit

Smart Investing From computerized trading terminals and electronic stock exchanges to online trading and satellite surveillance of physical assets, the investment industry has never been slow to harness the opportunities presented by new technologies. Tech and investing go hand-in-hand,...

AI: The Best New Technology in the Investor’s Toolkit

Smart Investing

From computerized trading terminals and electronic stock exchanges to online trading and satellite surveillance of physical assets, the investment industry has never been slow to harness the opportunities presented by new technologies. Tech and investing go hand-in-hand, and the latest development to make its mark on the sector—and potentially the most significant to date—is Artificial Intelligence, or AI.

One of the greatest strengths of AI is its ability to process and analyze vast amounts of data, quickly, efficiently and accurately, making the technology a powerful tool for making critical and time-sensitive decisions. As the worlds of investment and AI begin to intermingle, an increasing number of applications are presenting themselves, with algorithms helping investors make smarter decisions across multiple use cases.

What is AI?

It’s worth going back to basics and explaining what is meant by Artificial Intelligence. Investopedia gives a helpful definition: “The simulation of human intelligence in machines that are programmed to think like humans and mimic their actions”. But by harnessing a computer’s processing power, an AI uses algorithms to perform tasks far more quickly and more accurately than a human would ever be able to.

“Machine learning” is an integral element of AI, in which an algorithm is “trained” by being fed huge amounts of data, effectively making it more “intelligent” and enabling it to make more well-informed, reliable and accurate decisions. Sometimes an AI will be trained to perform a basic but laborious task, to achieve it more rapidly or free up human labor. In other cases, however, an AI is used to augment human skills, as the ability to process huge quantities of data helps achieve things that were previously impossible.

AI can be seen in industries as diverse as healthcare (where it is used to synthesize drugs or to aid in preventative care), manufacturing (predicting machine failures and increasing productivity), education (facilitating virtual classroom experiences) and logistics (monitoring and optimizing supply chains). The finance industry is no exception (one of the most common uses is automated fraud detection through monitoring of suspicious activity) and a recent survey by technology firm NVIDIA revealed that 83% of financial services professionals consider AI to be crucial for future success. There are numerous applications for investment…

AI for Investment

A recent report from Deloitte outlines the opportunities that AI presents for investment management, and highlights above all the added efficiency that the technology can bring to the industry. To summarize, AI can help to drive investment efficiency and generate higher returns, through its ability to recognize patterns and anticipate future events. Today, AI has the sophistication to create good rules for itself, meaning that it can make reliably optimal decisions.

It’s worth focusing in on four key areas where AI can help investors.

Algorithmic Trading

Proprietary algorithms can aid in trading by rapidly collecting and analyzing data about market conditions and price movements, using this information to carry out automated trades. These decisions are made at lightning speed, which makes them ideal for high-frequency trading.

Until recently, using machines to make trading decisions has largely focused on short-term investments due to the relevance of rapid decision making. However, as the technology (and our use of it) becomes more sophisticated, AI is now supporting long-term funds as well.

Portfolio Management

AI can help to optimize portfolios through a number of uses. It can create automated insights (by rapidly reading transcripts, for example) or map unexpected relationships between assets and market indicators. It can also monitor search engines for investment or market activity. Artificial Neural Networks (aka ANN, a type of AI) has been proven to be a superior prediction tool compared to linear regression models, due to its ability to handle the chaotic and dynamic nature of the markets.

Text Mining

Text mining and related syntactical analysis is a ubiquitous application for AI, but it has some powerful applications for investors. A machine can automatically scour news reports, social media content and other texts for information that could predict stock performance and market trends—and it can do so in a fraction of the time that it would take a human.

Text mining can also help with compliance management and regulatory reporting, as AI can extract the latest information far more accurately and efficiently, eliminating errors, and it frees up employees for other tasks.

Risk Management and More

One of the most crucial elements of investment is risk management, and it’s perhaps here that AI is the real game changer. When all the above use cases are considered as a whole, it’s clear that AI provides investors with improved compliance and risk management, by enhancing data analysis, accelerating decision making, removing human error, and helping to anticipate and mitigate unknown factors.

In addition to all the above, there are a vast array of administrative uses and back-office applications where AI can increase efficiency for every industry—it can even help with client outreach and lead generation by analyzing social media data.

Enhancement, not Replacement

In short, AI helps investors generate return by improving efficiency, providing better insights and enabling faster, more in-depth analytics. However, one last thing to note is that this should be combined with traditional financial data and analysis—and traditional, human staff.

Indeed, when incorporating AI into operations, a firm should think not in terms of “automated workforces”, but “augmented workforces”, continuing to recruit talent—and remembering that employing data scientists who know how to work with AI is just as important as employing the AI solutions themselves. Investors should also be looking to introduce AI in conjunction with other technological advancements, like blockchain technology, the cloud, and quantum computing.

With companies, governments and the public growing more accepting of a world where they interact with intelligent machines on a daily basis, it’s inevitable that AI will play an increasingly central role in every aspect of our life, and a truism that Artificial Intelligence and smart investing are the future of finance. Given the hugely positive impact AI can have on investment efficiency and alpha generation, this is something that every investor should embrace.