This is the second article of our series “How more collaboration could drive better investment decisions”.
← Part 1 — Data enables decision-making … if you have the right tools
Information and data have always been the foundation on which rational humans base their decisions. However, the more complex the situation is, the harder it is to gather the necessary data and insights to make the ‘right’ call. But too much data can also prove overwhelming and hamper decision-making. At Thread, our ambition is to challenge this status quo for the investment management industry.
For centuries, finding data used to be the issue
For a long time, obtaining the necessary information to conduct financial activities was a problem. It either didn’t exist or was hard to come by. For example, the premium of insurance contracts, first developed in the 14th century, were originally priced intuitively because there were no data on risks. Traders on the Amsterdam Stock Exchange, established in 1602 and the first of its kind in history, would glean information simply by talking to peers or merchants. Short-term speculative trading dominated and little energy was put into proof-checking or making sense of the data they were given. Then during most of the 20th century, investment professionals would spend the vast majority of their time sifting through annual reports and newspapers in order to find useful information. The analytical part of the process was limited to a few educated guesses about the sector or the company.
Then came the digital revolution
Everything changed in the 1990s. First, affordable personal computers and spreadsheet software such as Excel enabled individual investment managers to harvest large datasets and derive insights from them. Additionally, the democratization of the internet meant that data like financial ratios, rankings, and other financial information became commodities. As the access to data and tools to analyze them improved, investors dedicated increasingly more time and money to the analysis of data in the hope that acquiring more insights would translate into higher portfolio performance. Nowadays, they spend the majority of their time working on upstream and midstream processes and invest massively in faster computers and more sophisticated analytical techniques to improve their informational advantage.
Nowadays, we have a new problem: information overload
However, rather than solving the information problem, the investment community simply went from one extreme — the lack of data — to another — information overload. Investors nowadays are drowning under the overwhelming amount of data and insights that they read every day. There are several reasons why this is a problem.
First, it reduces the time investors can allocate to their main task: deriving meaningful investment decisions from actionable insights. With so much data available, their focus has indeed shifted from elaborating investment theses to producing and compiling information. During the many interviews that we conducted with professional investors, they repeatedly brought up:
- how time-consuming it was to find the right information on cluttered user interfaces.
- how tedious it was to process thousands of reports sent by research providers each day
- how frustrating it was to have financial models sitting in old excel files, losing their relevance over time
- how many investment ideas were lost in overflowing mailboxes
Several interviewees confessed that they increasingly felt like machines and that this ‘information race’ stripped away the most enjoyable part of their job — coming up with sound investment theses.
Second, more data make decisions less understandable. This is highly problematic given that, since the 2008 financial crisis, the activity of professional investors is subject to a very high transparency requirement. Fund managers need to be able to justify every investment decision they make to their hierarchy, their investors, or the regulator. However, the more data they pour into an investment decision, the harder it is to explain the main drivers of those decisions.
Finally, investing in data and analytical capabilities is costly. Spending on data sets has increased at a steady 27% CAGR for the past four years, and “fund managers globally may spend over $1.7 billion a year […] by 2020” leading-provider Bloomberg estimates. The cost of data rises because investors acquire new datasets, but also because the price of the existing datasets increases. In 2019, the Financial Times reported that brokers, fund managers, and other actors were increasingly vocal in their displeasure over the rising costs to receive information.
Conclusion
Most asset managers now face a conundrum. They know that the marginal benefit of additional data is now low. However, they also fear that if they don’t keep up, they may face an information disadvantage. As data providers are investing to provide alternative datasets, from geolocalisation to sentiment data, this problem is only going to worsen.
Part 3 — The beautiful synergy between data, collaboration, and communication →
