Startups Could Fundamentally Change the Way Big Investors Operate4 November, 2016 / Articles
Innovation has the potential to transform the investment industry. Small startup firms are already developing proprietary technologies — such as machine vision, deep learning, and other innovations —– that could help large investors evaluate opportunities and risks with far greater accuracy and efficiency than was previously possible. Yet the world’s largest funds are closed off from these innovations.
Research we have collected in recent months shows that pension funds, sovereign wealth funds, and endowments expect imminent breakthrough innovations in investment technology. But almost none of these institutional-investment giants have any policies in place for monitoring or engaging with the startups who are creating next-generation investment technologies.
The success of institutional-investment firms is socioeconomically vital: Their task is to grow the financial assets needed to fund retirements, development, education, scientific research, and many other capabilities associated with pensions, endowments, foundations, sovereign wealth funds, and the like. In short, we need the world’s biggest investors to connect with the world’s nimblest investment-technology startups. But right now that’s not happening.
In September 2016 we undertook a survey of nearly 300 endowment and foundation managers. None responded that their organization was “proactively looking” for startups that offer performance-improving investment technologies, despite the fact that 76% of them anticipate startups will deliver the next major “invest-tech” innovations. Likewise, in a more focused study of eight large public pension funds, we found that none are using startup companies as a main source for innovation. Instead, they tend to perpetuate the status quo: 75% predominantly rely on large, established vendors and relationships to source their investment technology. We have replicated these results in other surveys of C-suite executives at large public pension and sovereign wealth funds.
This disconnect is a major problem for the continuing development of efficient capital markets. Collectively, the world’s investment giants hold in excess of $70 trillion in assets, which represents the bulk of investable capital globally. Given their size and appetite for diversification, these gigantic investors are a significant source of financing for many companies and governments in the developed world, and their investment activities can and do move markets.
The lack of engagement is all the more perplexing due to the fact that the giants are unsatisfied with the performance of their current suite of technologies. How is this state of affairs possible? Large investors rely on an assortment of intermediaries to help them with their investment activities, including asset managers, such as hedge funds, investment banks, and consultants. This reliance has evolved because despite the enormous volumes of capital they control, most of these giants are strictly “firewalled” and cannot use the capital to fund actual operations, even if doing so would generate higher expected investment returns or lower risk.
Consequently, giant funds are often hamstrung by proportionally tiny operating budgets, which have historically forced them into the all-too-happy hands of intermediaries. These intermediaries generally charge significant fees, which affords them the luxury of building technological economies of scale, even when their investment returns are inconsistent and disappointing.
Another problem is that, just as the giants aren’t paying attention to startups, too few startups are thinking earnestly about the “boring” world of institutional investment, even though it is an industry ripe for massive disruption. Although “fintech” has recently enjoyed substantial popularity within the entrepreneurial community, startups in Silicon Valley and elsewhere focus primarily on consumer-finance problems, such as payments, peer-to-peer lending, crowdsourced fundraising, and other individual-level activities, rather than institutional-investment applications.
As such, the most promising next-generation invest-tech is emerging from startups that aren’t focusing, at least initially, on financial applications. Rather, they begin by tackling other pursuits, such as using satellites to track rainforest destruction or predicting social-media sentiment for brands.
The good news is that we see a trend of dynamic young businesses beginning to realize that the pattern-detection and extrapolative powers of the digital (and, in many cases, physical) infrastructures that they have been building and refining can be repurposed from Main Street applications to Wall Street. And, as has become the hallmark of today’s best startups, some have already begun the process of pivoting.
First, several startups are giving access to unconventional forms of data. Orbital Insight, for example, uses a global network of imaging satellites and specialized machine-vision and shadow-tracking algorithms to monitor: traffic turnover in retailer parking lots; the pace of construction for new buildings; plumes of effluent at factories; and vehicle payloads leaving mining sites, to name just a few examples. Such granular, real-time data on business and economic activity has never been so directly available to giant funds before, and it could equip them to more readily value risks and performance.
Second, deep-learning capabilities are sharpening the inferences that large funds can make. Companies like Skymind now have tools (increasingly open source) that allow deeper processing of conventional data, such as annual reports and filings, to spot irregularities, anomalies, and inconsistencies that might indicate fraud or underperformance.
Third, invest-tech that can mine social media and other “semantic” data streams is enabling sharper evaluation of companies’ intangible assets, such as customer loyalty and brand reputation. Tools like Predata have already shown strong performance in teasing out subtle relationships from social media in general, and the fact that more companies are relying on these channels for customer engagement means understanding the risks in such approaches will become a part of more large investors’ tool kits.
Fourth, widening availability of machine-intelligence algorithms and packages — e.g., TensorFlow and OpenAI — means that giant funds have access to computational firepower, allowing them to challenge (and empirically verify) established conventions in various industries, such as who is a competitor for whom. And rather than having to trust companies’ self-reports about what information matters most, investment giants can easily verify the factors that are most material for performance and make specific demands to have it be transparently disclosed.
We foresee that startups and large investors will soon become better at finding one another. When this happens, the value creation will be substantial. For instance, startups might be able to access some of the $2 trillion that giant institutional investors currently allocate to hedge funds and divert it to their own growth. An influx of that scale would dwarf the approximately $78 billion invested in startups by venture capitalists in 2015.
Moreover, the use of truly open innovation by the world’s large funds would spell deep disruption for the finance industry in ways that could genuinely advantage citizens and institutions for whom giant funds ultimately operate. As a result of this deepening disruption, the ways in which companies are valued and capital gets allocated could change forever.