For months now, I’ve been writing about the dramatic rise of Artificial Intelligence (AI) within the capital markets. In fact, given my multi-decade background in Investor Relations services, I’ve devoted most of my attention to the intersection between AI and IR.
With that in mind, it’s intriguing to consider how today’s most sophisticated institutional investors are utilizing AI and alternative data to continually add efficiencies, reduce costs, and comply with an ever-evolving regulatory landscape, all the while, increasing their incremental alpha.
MiFID II is making relationships more direct for buy-siders
Today’s unavoidably hot topic is MiFID II and its impact on research, trading, and corporate access. While we’re already seeing some significant changes, including reduced demand for and coverage of sell-side research, along with the rise of new DIY corporate access platforms and boutique research sources, there’s still a ton of uncertainty around how the triangular relationship between issuers, sell-siders and buy-siders will unfold. However, one thing is clear: both investors and issuers will need effective tools to navigate unfamiliar waters on their own.
Corporate access has long been the domain of the sell-side. Research firms would traditionally leverage their industry knowledge and “unique access” to c-level executives, competing against the buy-side for facetime with targeted companies; simultaneously taking advantage of the corporate issuer’s interest in research coverage to ultimately attract more investment dollars. It was a truly fortuitous (and profitable) cycle for the sell-side. But in today’s post-MiFID II world, the sell-side’s “middleman” role has been completely thrown into question.
We continue to see a dramatic increase in direct, one-to-one meeting sets between issuers and interested investors — without any sell-side involvement whatsoever — and there’s absolutely no indication (or reason) to think things will reverse course. In actuality, face-to-face communication with the buy-side is rapidly becoming the new way of doing business.
The rise in passives
It’s no secret that over the past several years, we’ve seen a massive rise in passive investments. According to a recent report from Morningstar, 2017 saw a total of $692 billion in net inflows into passive funds, while actively managed funds suffered net outflows of nearly $7 billion.
For active managers, this has translated into an increased scrutiny of fees and investment strategies, while also putting a more concentrated focus on non-correlated, risk-adjusted returns (or in other words, alpha generation). To be clear, this isn’t purely a long-only mutual fund phenomenon — hedge funds aren’t immune to this trend either. HFR says that since 2016, a net $60 billion has been withdrawn from hedge funds; while Deutsche Bank’s Alternative Investment Survey asserts that as of 2017, average management fees have fallen from the traditional “2 & 20” model (which hedge funds enjoyed for years), down to 1.56% and 17.3%, respectively, for management and performance-based fees.
Corporate access and alpha generation
Since MiFID II, the buy-side can no longer rely on outsourcing sell-side agents for research and corporate access. With all aspects of trading, research and corporate access now under great scrutiny, and cost management having to follow new transparency rules, now more than ever, the buy-side is forced to take corporate access into its own hands.
New AI and big data technologies are helping meet the demands of this quickly changing environment. A good example is Q4’s recently released AI Targeting, which enables institutions, funds, and endowments to quickly and easily identify the most attractive stocks for building portfolio parameters, and position them with those issuers most amenable to pitching their story. It’s a first of its kind model that leverages deep capital markets intelligence and machine learning capabilities, to match institutional investors with corporate issuers.
Our proprietary algorithm generates probabilities and matches “scores” between institutional investors and publicly traded companies, analyzing such data points as company fundamentals, financial ratios, equity and options trading, sentiment and momentum, volatility, and relative performance. By combining company fundamentals with investor portfolio characteristics, and then overlaying market-timing analytics, we’re able to put the right investors in front of the right issuers, at precisely the right time. For both buy-siders and issuers alike, this means not only dramatically improving ROI in investment targeting and corporate access, but improving workflow efficiencies.
In addition to creating the AI Targeting scores themselves, which are basically a product of a probability score and matching score (how likely Firm X is to buy ABC and their compatibility), the algorithm dives even deeper. These models are able to predict optimal share size and concentration and identify the key underlying factors that are likely driving the investment thesis for any given firm or fund.
Think of the technology as a “Robo-Analyst.” It’s not only able to understand which securities are most likely to be attractive to you over the near-term, but also which underlying fundamental and market timing factors are driving this analysis (and conversely, which might be least attractive). Armed with this kind of predictive intelligence, you can feel confident in the names you present to your investment teams and lead the conversation with the most relevant points for your internal audiences.
Solutions driven by big data also provide predictive analytics on money flows. AI Targeting can forecast which stocks will attract which investors, combined with a “confidence score” and the predicted share impact. The technology is able to see patterns and unearth predictive intelligence for the securities and sectors most likely to attract new money in the coming months.
Knowledge is power
Over the past 12-18 months, there’s been a dramatic rise in buy-side use of alternative or “Alt” data, in combination with artificial intelligence. Whether driven by new regulatory statutes, client demands, or the need to find alternative ways to generate alpha and reduce the cost of targeting efforts, the Street is clearly moving in this direction.
Understanding where money is flowing, which investments are best-suited for your particular fund and why, and matching the right investors with the right issuers at the right times, is key to streamlining your corporate access practices, as well as identifying the highest quality investment opportunities possible. Ultimately, this all leads to saving time and money for your entire organization.
Adam Frederick is the Senior Vice President of Intelligence at Q4 and blogs regularly about trends in investor relations, artificial intelligence, and alternative data.