Financial Institutions May Recover Lost Glory If They Aggressively Adopt Technology Fee Compression As Far As The Eye Can See Long gone are the days of white-collared shirts, suspenders and fat fees. The Financial Services industry is reducing headcount across the board. No pocket of the capital markets is immune. Investment Banks, Depository Institutions and…
Three logical, prospective M&A trades (Fintech & Enterprise Software), that make sense for the next 12-36 months. Learn more about each target and prospective acquirer at CEORater.com …
For the past few years I’ve poked around the machine learning (“ML”) and artificial intelligence (“AI”) space. I advised Boston-based DataRobot back in 2014 when they started to build their machine learning platform. I’ve thought about how we at CEORater may leverage ML to score CEOs and companies. Typically when we read about ML and AI it’s from the perspective of a pure-play vendor who markets and licenses its platform across multiple industries for a variety of use cases. Often the use cases we read about are focused on “power users” – people who have a PhD in Statistics or some similar quantitative background.
Recently I had the opportunity to demo SS&C’s (tkr: SSNC), new back-office, middle-office platform (“Singularity“) which has machine-learning, artificial intelligence and robotic process automation (“RPA”) at its core. This was my first opportunity to observe a fintech platform that was built from the ground-up to fully-leverage ML, AI and RPA.
From a background perspective, Asset Management firms of all flavors (small, mid-sized and large, traditional, hedge funds, private equity etc.), Fund Administrators and Insurers use a variety of SS&C products and services to value assets (equity and fixed income securities, derivatives, bank loans, private placements and real assets to name a few asset classes)/ strike an NAV, settle trades and report on asset holdings. The company’s Singularity initiative will replace siloed products with a common ML-based core layer that will have modular AI and RPA services that sit on top.
Multi-tenant machine learning is a significant competitive differentiator. Some readers pride themselves on identifying businesses that have a competitive “moat”. For non-investors a “moat” is a source of sustainable competitive differentiation. Challengers who wish to compete against companies with established moats best be prepared to completely shift the paradigm and render the moat obsolete. You’re simply not going to spend your way around, over or through a moat. Brute force won’t work. If any company ever had a moat, SS&C has one in the world of portfolio accounting systems.
SS&C’s moat is about to get significantly wider and deeper as Singularity is rolled out. This is in no small part due to the multi-tenant machine learning layer. This means that as Customer X has an experience that requires a “learning”, the benefit of that learning is enjoyed not only by Customer X but also by the other customers on the platform. This multi-tenant element to Singularity’s machine learning layer is a powerful scale differentiator primarily for three reasons:
- Large installed customer base: SS&C has a great many customers and users – therefore more opportunities for machine-driven learnings – the benefits of which accrue to all SS&C Singularity customers.
- Purpose-built from the ground up: SS&C has incorporated machine learning into Singularity from Day One, providing the company with a significant and sustainable advantage over competitors who may try to retrofit a third-party’s machine learning layer on top of legacy products and services. Retrofitting legacy technology simply can not be as effective from a throughput and efficiency standpoint as a new, modern-architected platform.
- Cost prohibitive: It’s not an insignificant dollar amount that’s required to build a modern, ML/ AI/ RPA-powered Fintech platform from scratch. To replicate Singularity from a domain-expertise and technology perspective would be cost prohibitive.
VC’s would be wise to avoid trying to disrupt this market. As I see it, the only way to replicate what SS&C has built would be to acquire the company.
Regular readers know that we are partial toward Technology Founder CEOs vs. hired CEOs as a general rule. Our experience is that founder CEOs are generally better than hired CEOs at anticipating customer market needs, in many cases before customers know they have a need. Founder CEOs care deeply about details of the business that a hired CEO may not give more than a casual glance. Founders in many cases work to leverage their smart senior business leaders whereas hired CEOs may feel threatened by a direct report’s potential. We could go on.
Our CEORater Technology Founder CEO Index has performed well year-to-date through December 6th enjoying a Total Unweighted Return of 14.2% and a Total Weighted Return of 17.1%. The comparable benchmarks returned 5.1% and 4.4% on an Unweighted and Weighted basis respectively. You may access the detail HERE.
Speaking of Technology Founder CEOs, we recently hosted a podcast with SS&C Technologies (ticker: SSNC) founder & CEO Bill Stone where we discussed M&A strategy, SS&C’s decentralized management approach (another core principal of ours) as well as SS&C’s “Singularity” artificial intelligence (“AI”) and machine learning (“ML”) initiative. In the case of SS&C, we believe that AI and ML will drive efficiencies across back office and middle office-related products and services – enabling customers to drive incremental throughput with less effort. Further, AI & ML has the potential to create revenue and EBITDA opportunities for front-office customers (facilitating deal sourcing as an example). You may access the episode below:
Technology news items that caught our attention this week:
U.S. venture capitalists didn’t fund this Duke professor’s powerful facial recognition platform, so the Chinese government did: Link
Gamers rule the world. Now they have their own stadiums: Link
Human Capital is Key
“It’s people! Soylent Green is people!” shouted Charlton Heston’s Robert Thorn in 1973’s Soylent Green. Fast forward 45 years and people remain central to the process. Although the process we refer to isn’t recycled human foodstuff but rather the global economy where Intellectual Capital provides economic sustenance and Human Capital is the key ingredient (Intellectual Capital = Human Capital + Structural Capital + Relationship Capital).
Grist for the Mill
It’s only a matter of time before Technology giants begin to reach into public schools in an effort to identify and recruit top-tier talent in an Intellectual Capital-driven global economy.
Technology’s Four Horsemen – Alphabet, Apple, Amazon and Facebook – hired 247,714 net new employees in 2017, up 89% from the previous year’s figure of 131,196. Amazon alone accounted for 91% of 2017’s total and 84% of 2016’s total (this makes sense given the nature of Amazon’s retail-centric, distribution-heavy business model).
Technology companies require an enormous amount of human capital and brainpower. This is especially true of large technology companies that work to define new market opportunities and use cases. Waiting for the U.S. K-12 public education and university systems to produce inadequately trained professionals is both a suboptimal outcome and supply chain bottleneck. Therefore, we expect for companies such as the Four Horsemen to become increasingly aggressive and systematic in their approach to training and recruiting young people.
We have experienced early green shoots of this phenomenon with Peter Thiel’s “Thiel Fellowship” a foundation that awards $100,000 grants to high potential young people. Those accepted (104 fellows and alumni, 2,800 application last year), to the two-year program learn how to write code and build companies. Young people skip or step out of college to become Thiel Fellows where in addition to grant proceeds, Fellows receive support from the foundation’s network of entrepreneurs, investors and operators.
Another example comes from my personal experience in China 2006-2011 where a number of the large China-based IT Services companies set up company-owned “universities” to train recent college graduates in an effort to better prepare them for the type of work that they would perform on behalf of clients. My view is that these companies will reach further back into the student supply chain and begin to recruit and train students during their junior high and high school years.
A misconception that many have is that an engineer fresh out of college can hit the ground running at optimal efficiency and drive massive value for companies. That’s hardly the case. Universities do a poor job of preparing students for life in the real world. It makes enormous sense for companies to actively invest in the U.S educational system both at the K-12 and university levels. Short-term operating profit margin dilution will pay dividends over the long-term in the form of new differentiated products and services. To ensure a worthwhile outcome it is paramount that companies take a systematic approach to execution. If nothing else Alphabet, Amazon, Apple and Facebook excel in measuring outcomes and re-calibrating where necessary.
No Teachers Required
Given what we have posited it would make sense for the Four Horsemen and others to get involved in public education early in students’ academic careers. Further, it would be logical for companies to seek to influence the academic experience as much as is necessary to maximize the probability of optimal outcomes for both students and companies. Therefore, it is not unreasonable to expect that the Four Horsemen and a few select others will eventually shape student curriculum — particularly in Math and Science. This may range from content creation to teaching methodologies to the act of teaching itself. Teachers’ Unions ought to be concerned. From a technology standpoint it would not be difficult to replace public school teachers nor college professors with machine learning platforms wrapped in friendly AI skins. AmazonGo is already doing this with retail checkout lines. It’s less a question of “how?” and more a question of public will.
Yes if You Ask Us While AT&T moving to acquire Time Warner and Disney (and Comcast?) moving to acquire Fox are interesting deals, it’s more interesting to us what the next chess move may be in a world that increasingly values content (live sports and premium original content in particular). We recently wrote about and…
It’s fun to speculate. What if Google parent company Alphabet were to acquire Walmart in an effort to better compete with Amazon? One of the advantages that Amazon has in an AI-driven world is a fully integrated retail experience. Amazon customers may speak buy orders into their Alexa-powered smart device – “re-order paper towels” -…
I have previously been critical of Apple’s AI effort. Siri lags both Google and Amazon (Alexa) in terms of speed and accuracy. Apple’s Shazam acquisition is good for consumers in that it bundles a service people enjoy with Apple Music. More importantly, the acquisition will drive more Siri queries – something Siri needs to get itself into fighting shape to better compete with Google and Amazon. Learn more by listening to our recent CEORater Podcast: Apple’s Acquisition of Shazam Will Benefit Siri