Sentieo recently partnered with the Harvard Business Review (HBR) to publish a briefing paper explaining how research powered by artificial intelligence (AI) can provide a source of competitive advantage for investment firms. The paper highlighted how inefficient research processes can hinder a firm’s pursuit of alpha and while technology is part of the cause, intensifying the flow of information, it can also play a role in the solution.
In this first of a series of three blog posts summarising the paper’s findings, we explore some of the challenges that analysts face when researching investment opportunities.
Companies across all industries struggle with the sheer volume of information they must process. Research by HBR in 2019 showed that 82% of respondents struggled with analyzing unstructured data and 77% relied on manual methods. The burden is even greater in the investment industry due to the regulatory demands of listed companies. The Securities and Exchange Commission alone processes around 3,000 filings each day.
Many analysts also need to research industry trends to build a credible investment thesis. That means combing through additional layers of information. For instance, one database of North American manufacturers covers half a million suppliers and has published 300,000 articles.
All this information comes in different formats, which makes it hard to collate. Analysts typically monitor a range of sources when researching a company. A news story on the Wall Street Journal may prompt an idea which requires further investigation through search engines, data terminals and reports. That’s why the information is known as unstructured- it comes as spreadsheets, PDFs, videos and even social media posts.
In the absence of a central platform, most analysts build their own system to track developments, manage the information they gather and share it with colleagues. How much of it gets lost in the process is anyone’s guess.
To uncover insights, analysts must spend countless hours sifting through the information manually. But that’s hardly an effective use of their time. Minor distractions, such as searching for an email, on their own may not cause much disruption, but they add up. Valuable nuggets of information could also be hidden in instant messages, Slack channels and transcripts from virtual meetings. These distractions eventually affect an employee’s happiness and productivity, especially when that employee is a highly qualified analyst.
You didn’t hire these well-paid individuals to organize information, you hired them to analyze it and come up with actionable ideas which will help your firm deliver benchmarking-beating returns. After all, information inefficiencies lead to alpha which sets active managers apart from passive investments like exchange-traded funds and index trackers. This added value has become particularly important as money flows out of actively managed funds and into passive funds.
Analysts need access to tools to do their job more efficiently, but the investment industry has traditionally been slow to adopt new technologies. So in the next blog in this series, we’ll explore how AI, machine learning and natural language processing can help to ease the burden of information overload. Alternatively, you can download the full briefing paper here.