The amount of data that investors have at their fingertips today is daunting and vastly expanding the way investors view the world and where they put their money. But there’s a challenge that comes along with all this information: it doesn’t come in a perfect package. Much of this data is unstructured, unwieldy, and overwhelmingly time-consuming to digest and make sense of. Artificial intelligence (AI) and machine learning allow investors to comb through this messy data to rapidly tease out insights they might never have had access to otherwise.
Among these insights is a way to help improve portfolio performance in real-time. Imagine taking disparate pieces of information like the number of construction permits granted in China, sentiments picked up from online employee reviews, and the number of shoppers purchasing online and in-store for a particular retailer. Then, when layering in millions of other data points—like research reports, quarterly earnings, and news items—the depth and breadth of information at the fingertips of investors is nearly endless. AI allows investors to quickly parse and analyze this data, enabling them to make smarter investing decisions in a fraction of the time.
Along with these insights, machine learning offers investors a way to help improve their portfolio risk management. Interactive Brokers (IBKR), a Greenwich, Connecticut-based securities firm, gives investors this ability with its Risk Navigator tool. A spreadsheet-like interface allows investors to identify their risk exposure right at the portfolio level, with the option to drill down further into more detailed levels of intelligence within multiple report views.
Other benefits of IBKR's Risk Navigator:
View overall risk exposure as a single number while monitoring the total risk and direction of risk associated with a single position.
View a portfolio risk for multiple asset classes and assess specific risk slices of a portfolio, such as risk by position, risk by underlying, and risk by industry.
Create an editable "What-If" portfolio to see how a risk profile might change based on hypothetical adjustments to their actual portfolio.
Another example, BlackRock, the money management giant, has developed an operating system called Aladdin Risk Platform. It uses machine learning algorithms to provide users with risk analytics to monitor risk in their portfolios. BlackRock says it can automatically screen over 2,000 risk factors per day, something a human would not be able to do.
The ability to analyze reams of data and tease out useful and actionable insights is among the key benefits of AI when it comes to portfolio performance. As the amount of available data increases, analysis becomes more challenging. According to research firm New Constructs, average SEC filings have grown to more than 200 pages, becoming increasingly complex and time-consuming. Accounting rules are also constantly changing, making them increasingly more difficult to keep up with.
As a result, AI enables sophisticated investors to have a whole new perspective on the actions they may consider taking with their portfolios. IBKR’s PortfolioAnalyst is a robust performance reporting tool that provides investors with consolidation, tracking, and analysis across different financial accounts. At a glance, it lets users view everything in one place from a desktop or mobile device. Equally important, users can link their investment, checking, savings, credit card accounts and more to PortfolioAnalyst, even if they’re held at different institutions.
Other ways AI is making this happen:
Perform advanced stock screening to identify investment opportunities that fit an investment preference and carry a higher-than-average chance of outperforming the market.
Take disparate sources of information (official filings; company filings; news searches; historical data) and absorb and weigh the relevant insights to arrive at a proposed course of action.
Create dynamic models that adapt to the data at hand through deep learning—a function of AI that imitates the workings of the human brain for decision making.
When it comes to making investing decisions, AI and machine learning are helping sophisticated investors address two critical issues: trading risk and efficiency. The ability to screen for the right data points at the right time and in a way that makes the most sense means investors are able to trade with the best information at hand.
AMERICANS say they expect to use an AI-Powered roboadvisor by 2025
A great example is IBKR’s IBot. This natural language trading bot leverages artificial intelligence and machine learning to give investors the edge they need. And in a world where nearly 60% of Americans say they expect to use an AI-powered robo-advisor by 2025, that trend will only strengthen. IBot lets investors ask for information any way they choose. The AI technology enables IBot to respond to the countless ways an IBKR investor might ask for information. It then serves up that information, including anything from charts, orders, company fundamentals, pricing data, and more.
AI will continue to evolve and provide new ways for investors to search, distill, and refine the reams of available data. It will allow investors to explore new markets and products by finding correlations between factors that humans might not be able to detect.
AI and machine learning will likely never fully replace humans in the investing process. But these advanced technologies are enabling sophisticated traders to become more informed, more efficient and better able to spot opportunities than ever before.