[Product Release] AI Targeting is set to revolutionize the European market
14 May 2019
By Marla Hurov
Following a successful debut in the US market, Q4 is now introducing AI Targeting to Europe. Powered by Q4’s leading-edge artificial intelligence (AI) engine, this next generation tool leverages deep capital markets intelligence and machine learning capabilities, to revolutionize how IR teams target new opportunities. Engineered with 25+ billion individual data points, and based on three years of research and 10 years of backtesting, it’s the most advanced investor targeting solution the European market has ever seen. This industry-first tool is designed to maximize the accuracy and quality of investor outreach.
AI Targeting drives unprecedented accuracy for IR professionals, by predicting which firms/funds have the highest probability of purchasing/selling a given security within the next 90 days. It also precisely identifies the crucial underlying investment drivers, specific to every firm, fund and stock. Through deep analysis of historical correlation and regression, the AI algorithm generates a combined probability and “matching” score based on more than 700 datasets.
Seamlessly integrated with our innovative IR CRM, Q4 Desktop, AI Targeting is also the ultimate companion for planning NDRs and conferences. From updating contacts, to setting up meetings and generating tear-sheets, you can manage and track targets across your entire pipeline of investment opportunities. You can also leverage proprietary heatmaps (across Europe and North America) to help visualize and drill into geographic concentrations of high quality, ready-to-buy targets. Customize your search by variables including quality, AUM, style, type, and peer ownership.
In light of this release, I sat down with our Q4 Euro team to explore how AI Targeting empowers IROs in a post-MiFID II ecosystem.
Closing the Sell-Side Gap: Connecting Corporates and Investors
With MiFID II in play, it’s never been more critical for corporate issuers to be proactive about connecting with institutional investors. According to Amit Sanghvi, Q4’s Managing Director for Europe, “IROs are realizing that brokers just can’t put them in front of institutions like in the past.” He adds, “brokers are categorically telling investors they can no longer monetize certain investors.”
This reality extends to broker-organized conferences. Amit cites the example of a large-cap Q4 client who had been organizing, in partnership with multiple brokers, a successful annual “sector” conference which attracted over 20 corporates and 150 institutional investors. This past year, however, the conference suffered a staggering 30% drop in buy-side turn-out. They considered cancelling the event altogether, but instead, decided to set an industry first by organizing the event themselves. Amit says they reached out to Q4 to help bridge the sell-side gap, with our “CRM tools and AI-driven algorithmic analysis that deliver high quality, compatible buy-side targets.”
Old School Targeting: Brokers and Screeners
Over the past several years, an IRO’s arsenal of targeting tools and ancillary support has been undeniably limited. IR professionals have largely relied on brokers. But since MiFID II, brokers no longer have the same quality of relationships nor the ability to connect the buy and sell sides as effectively as before. Not to mention, brokers historically haven’t always had a company’s best interests at heart. According to Sam Cockerill, Q4’s Senior Director for Europe, “At the end of broker arranged roadshows, corporates are often left with the feeling that they’ve met with tier one clients for their brokers, rather than tier one investors for the company.”
The search for potential investors has also traditionally involved primitive buy-side “screeners” or basic fundamental matching, which typically look at an investor’s style of investment and location. The truth is that the output is often as generic as matching a growth investor with a growth company. Sam says that “it’s a rather crude method of screening an investment universe. Funds don’t actually act by pure characteristics like growth or value. Issuers don’t always fit these profiles perfectly either.”
Amit adds, “Peer analysis might simply tell you who doesn’t invest in you or who is underweight compared to your competitors, but it doesn’t tell you the reasons why they haven’t invested in you. Screeners are very basic. They don’t analyze the key drivers for investment decisions and where you align.”
Next Gen Targeting: Matching the Right Investors at the Right time
Now more than ever, corporate issuers need to improve the quality of their meetings with more quantitative approaches. Clearly, relying on the qualitative perspectives of a broker or the basic output of screeners is no longer enough. According to Christopher Jones, Director of Corporate Sales at Q4, “our algorithm produces results based purely on hundreds of data sets, without introducing any human bias. It also takes screening far beyond the next level, by analyzing billions of data points to determine the probability of an investor taking a position in a firm’s stock. For the first time, IR professionals can leverage advanced statistical rationale for meeting with potential investors.” Chris adds, “The release of AI Targeting for Europe speaks to Q4’s long history of investing in the most innovative and results-driven technology to analyse a stock’s performance.”
He points to the example of analysing a company’s shareholder base, “it’s been widely accepted that you can at best get monthly analysis on your shareholder base. That’s been the case for a long time, to the point where IROs have started to lose faith in its value and accuracy.” Q4 began pushing these boundaries with the earleir release of Continuous Shareholder Analysis in the UK. It enables a corporate to look at their register in as close to real-time as possible. With their pulse on market reactions, they can continuously align their shareholder mix with company objectives. “Now coupled with AI Targeting, the technology performs the deepest possible dive into the data.”
Essentially, AI Targeting looks at patterns of investor behaviour and market conditions, not only quantifiably identifying the strongest investment opportunities in the near-term, but also the drivers behind these patterns. This is based on more than 700 key variables, including total assets under management, turnover history, corporate style, and portfolio characteristics. Sam summarizes, “our scoring system analyses funds globally, in combination with their top investment drivers, to precisely and comprehensively tell an IRO who to meet, when and why.” IROs can finally focus on the investors who will add the most value and stability to their current shareholder base. Moreover, knowing the top factors that influence a given investor, can effectively arm them with the crucial talking points to strategically position their company and capture the hearts and minds of the buy-side.
According to Amit, “nobody else analyses and integrates over a decade’s worth of fundamental and economic data, as well as fund and disclosure information, covering every single market worldwide. That’s more data than any human could possibly handle.” AI Targeting leverages true AI machine learning technology, rising above all of the noise in the AI space. It continuously adapts to any scenario and improves its performance over time. He concludes, “the machine objectively analyzes patterns of investor behaviour, synthesizing past and current market conditions, to make increasingly precise real-time predictions. It’s truly avant-garde and scientific. The results are unprecedentedly accurate, sophisticated, and immediate. Nothing rivals AI Targeting in the European market.”
Marla Hurov is the Content Marketing Manager at Q4 Inc and blogs regularly about trends in IR and digital communications.