Predictive Analytics 2.0 Is The Next Big Thing In Investment Banking
Next Generation Algos Will Propel Predictive Analytics Next Big Leap
The investment banking industry is no stranger to big data analytics. The shift from short term, human-based trading decisions to algorithmic ones gained a foothold 15 years ago and never looked back. The machines didn’t just win, they dominated. Over 90% of trading is now conducted by automated stat/arb trading programs able to calculate probabilities much faster than our reptilian brains ever could. But what comes next? How will the next iteration of predictive analytics play out now that the algos are largely cannibalizing each other?
The answer in a nutshell: they evolve. They simply must now that declining trading profitability is the new normal. As falling human trading volumes (a.k.a. the lemmings) and narrowing technology advantages take shape, a classic battle for industry supremacy is brewing. Firms which master predictive analytics 2.0 will reap the rewards of billions of dollars in profits. It’s the ultimate high-stakes game of poker, where the first to bring a powerful, scalable solutions win all the chips.
To exemplify how competitive the trading landscape is, consider that some trading firms are exiting High Frequency Trading (HTF) altogether. The iconic financial blog ZeroHedge—who has been front-and-center in covering the HTF wars since its inception—has documented this well.
In November 2016, ZeroHedge reported the case of Misha Malyshev, the genius astrophysics PHD who founded and leads Teza Technologies. It seems couldn’t replicate his previous success at Citadel, which earned the Goliath trading firm over $1 billion in the late 2000’s. Ultimately, Teza sold a large portion of its HFT assets in mid-2017 as revenues from the prop trading business declined from about $250 million in 2012, to $80 million in 2015. The reason? Increased HFT-free exchange competition hammered revenues and margins, while retail traders remained in hibernation. As Misha Malyshev under-whelmingly stated, “Generally, it is harder to make money”
Further confirmation of HFT’s profitability troubles comes way of industry heavyweight Virtu Financial (NASDAQ:VIRT). After crushing it with exploding YoY revenue growth stretching back to the mid/late-2000’s, growth has been hard to achieve. According to Macrotrends, operating income, net income and total revenue stagnated badly in recent times. This grim reality prompted Virtu to acquire rival KCG Holdings in 2017. Adapt or perish.
It’s not only diminishing HFT returns leading the predictive analytics revolution. As AI gets more advanced, a critical shift from hindsight to foresight predictability is occurring. That is, intuitive programming is close to predicting future asset dislocations ahead of time, before actual events take place. Imagine the king’s ransom financial institutions would pay for such knowledge.
In essence, we’re in a time where Steven Spielberg’s iconic futuristic Sci-Fi masterpiece Minority Report is meeting Bay St. head-on. But instead of pre-crime interdictions, we’re talking about pre-investment ones. The first companies to bring powerfully accurate predictive solutions to market will reap the substantial rewards.
No longer does “peeking” at stock orders to front-run clients generate the requisite revenue growth needed to offset the massive CAPEX upgrades necessary to stay ahead of the game. Institutions are now looking at ways to predict trades before they happen—and they’re investing billions of dollars to do just that.
Data, Data Everywhere
Fortunately for investors, there is an investment worthy, pure-play AI company at the forefront of the predictive analytics revolution in Canada. Not only are they pioneers in the space, they have multiple sources of revenue streams and no shortage of suitors clamoring for their technology.
To good to be true? That was my initial reaction. But upon reviewing the company’s product portfolio, along with conversations with upper-management, I’ve become a believer.
The company in which I speak is called Analytixinsight Inc. (TVE:ALY). Their artificial intelligence platform transforms data into narratives—literally. Analytixinsight’s online portal, CapitalCube (www.capitalcube.com), algorithmically analyzes market price data and regulatory filings to create insightful, actionable narratives and research on approximately 50,000 global companies and ETFs.
While the company offers traditional asset correlation research standard in the industry, increasingly, the company’s algos are able to predict future corporate events with uncanny precision. Such things as future dividend direction and acquisition probabilities are now in-play. Analytixinsight has even built a pre-revenue analysis tool to predict the future cash burn rate of early-stage mining companies. Not only is that powerful, that’s extremely useful. And it’s all available for retail and institutional clients in an SaaS subscription model which is both affordable and intuitive.
However prescient their predictive analytics technology is, that’s only one piece of the product equation. Analytixinsight predictive capabilities are also extending in Big Data’s traditional domain of delivering targeted marketing solutions gleaned from the data they derive. In a sense, it’s not much different from what Facebook and Alphabet are doing, except on a smaller scale.
But not too small: An agreement with Intesa Sanpaolo (roughly the size of the Bank of Montreal) to migrate approximately 8 million mobile banking users in 8,000 retail branches to Analytixinsight’s Marketwall mobile platform was announced in July 2017. This gives the company potential access to millions of retail investor data, and acts as a stepping stone to enable complete trade execution on a secure mobile platform. Deals with Samsung, Borsa Italiana and the London Stock Exchange to preload StockWall on Samsung smart devices ensure visibility. It’s an area where lots of potential revenue streams can be actualized.
Furthermore, Analytixinsight is further focusing on developing blockchain solutions to streamline the derivative settlement cycle. The days of T+3/T+2 settlement dates in Canada are drawing to a close. Within the next 7-years, archaic human-based back office settlement process will likely migrate to the blockchain, saving firms billions in the process.
But developing a robust backend solution to handle millions of transactions is not an easy task. Analytixinsight is getting ahead of the curve by attempting to produce a viable platform solution it can license. Whether that’s in house or through partnership is unclear, but the demand is certainly insatiable.
At this point, the company’s blockchain intentions are too conceptual to be priced-in to the company’s valuation. But they do provide that potential game-breaking catalyst to propel the stock price should a viable platform be developed. With existing banking and equity exchange partnerships in Europe, Analytixinsight has the infrastructure in place to live-test blockchain solutions as they are developed. These relationships provide a substantial edge vis-à-vis competing blockchain companies without existing vertical vendor partnerships.
Market Data And The Upcoming Paywall
For years, investors have been spoiled by a plethora of free financial data sources. Websites like Yahoo! Finance (Canada) and Google Finance have provided platforms robust enough for the needs of most retail investors. But if Analytixinsight V.P. of Corporate Development Scott Urquhart is correct, that window is coming to a close.
Scott informs me that formerly-free services are about to employ a “paywall” model similar to that employed by Big Media providers such as the New York Times, Washington Post, and Financial Times. The idea is to charge investors monthly fees to access generalized data, and/or singular fees to access individual reports. Either way, Big Media is looking to offset insufficient advertising costs and bring profitability back to divisions which have underwhelmed.
As it turns out, this paywall model plays exactly into Analytixinsight’s hands.
Currently, Analytixinsight’s CapitalCube division publishes more than 3,000 articles daily and tracks about 2 million user sessions per month. Its content partners include Yahoo! Finance, the Wall Street Journal, Thomson Reuters, Euronext stock exchange, Tel Aviv stock exchange, and Africainvestor.
As the paywall structure becomes adopted, there should be further leeway for Analytixinsight too accrue greater licensing fees for its service. Where Big Media revenues increase, the content providers are sure to follow. Analytixinsight should soon benefit from an inevitable trend which will become increasingly obvious in the quarters ahead.
The advent of Predictive Analytics 2.0 is upon us. This trend isn’t simply materializing in the financial industry, but throughout various sectors in the economy. Investment banking (including retail investing and research) is just the tip of the spear because investing, by nature, is predictive. Thus, traditional means of valuing assets through peer-to-peer analysis—while still important—is poised to take a backseat to foresight analysis as AI capabilities grow. Darwinistic principles are at play here.
In our view, Analytixinsight provides the perfect pure-play segue into the space. Unlike other financial institutions conducting similar initiatives, Analytixinsight’s activities are solely involved in the predictive analytics space. There’s no loan book risk, subprime credit exposure, or counterparty risk. The company simply provides products and services which help institutions make better investment decisions.
And that’s a value-add people will gladly pony up for in an age where making the correct investment decision has never been so difficult.
Disclosure: Neither Midas Letter Publishing Group nor the author own any financial interests in the profiled companies.
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