Alphacution defines technical leverage as the difference between revenue per employee (RPE) and technology spending per employee. In the parlance of our T-Greeks benchmarking framework, this difference is also known as T-Spread. I stumbled over the chart below - 50 companies in the S&P 500 with the highest RPE rankings for 2016 - recently and thought it would be notable to add to the knowledgebase. Since our modeling and analysis currently focuses exclusively on companies related to the financial services sector, much of what we find in this exhibit provides illuminating context. Source: Craft Clearly, energy and healthcare companies dominate the RPE metric, with 3 companies producing astonishing RPE levels greater than $5 million. Only 3 companies from the Financials sector (2 insurance - Aflac, XL Group; and, 1 exchange - CME Group) make this list. From our own modeling, the highest RPE we have found to date is Virtu Financial - a high-frequency trading firm - with a 2016 RPE of $2.8 million. Among the world's major banking groups, Goldman Sachs [...]
Brain drain - in this case meaning the loss of valuable human capital - is one of those silent malignancies in an organization that is difficult to measure, and the impacts from which are typically not realized until the damage has already been done. With the global banking sector - and its constituent business segments, from retail banking to wealth management to capital markets - still in the midst of unprecedented and persistent transformation, the risk of ongoing losses of intellectual capital and corporate memory that leave via the elevator each day is still quite high - or, at least, it is perceived to be so. (The knock-on effects to the supply chain are notable here, as well.) It is largely for this reason that we have been monitoring and measuring various headcount-dependent metrics in the financial services ecosystem: Interesting and telling on a per-company basis, fascinating and illuminating of broader trends on a composite basis. The former being a weaker intelligence signal, the latter being a much stronger signal. So, here's [...]
Well, it would have been the Top 10 investment banks, but @Barclays doesn't publish quarterly headcount for some reason. Maybe they will help us fix that. Anyway, for the Top 9 investment banks, total headcount is down 13% from its peak in Q3 2011. And, with at least 2 of the 9 - @Deutsche Bank and @CreditSuisse - reporting significant headcount reductions for the road ahead as part their year-end 2016 financial releases and 2017 guidance, it's not much of a stretch for us to predict that the Wonkavator is highly likely to travel further back in time than year-end 2006 (see below). I just want to let this picture dangle for a bit without much comment. We will be revisiting and significantly expanding this analysis in the weeks and months ahead as we roll into the development of our 2nd Annual Global Bank Technology Spending study. Stay tuned...
If you are only interested in reading hyperbole-laced stories about the latest shiny things in #fintech innovation, then what follows is not for you. But, if you actually care about innovation that results in real impacts, then we invite you to keep reading. From the following angle, something changed around mid-2012 at @GoldmanSachs. Arguably, the groundwork for such change was laid prior to that time, but the impact of that groundwork (at least to observers like us) didn't become noticeable until the end of Q2-2012 when a metric that we are starting to track much more closely began to break out. Here's the setup: In an article published on February 7, 2016 by MIT Technology Review, "As Goldman Embraces Automation, Even the Masters of the Universe Are Threatened," a key statement made by Marty Chavez, the company’s soon-to-be chief financial officer and former chief information officer, caught our eye: "Goldman has already mapped 146 distinct steps taken in any initial public offering of stock, and many are 'begging to be automated.'" Our [...]
It's March 25, 2016 - and I crack open the newly minted 10-K from our friends at Virtu Financial. The equivalent of that new car smell wafts northward from its fresh digital pages. The anticipation is palpable. With years of intense focus and vigorous debate on the mechanics of #HFT - and the jealous wonderment surrounding its stratospheric profitability - it is both rare and puzzling that the public should get a real, data-driven look inside to support or debunk the mythology of this ultra-secretive corner of the global financial landscape. Searching within this fresh set of data, I update our model - and the output creates one of those WTF cognitive dissonance moments. After all, isn't the heyday of HFT over?! Haven't numerous high-speed shops consolidated or folded? As a refresher, the vid below is what we were saying back in July 2013 (while at Tabb Group): Hello from 2013! Struggling is not what's going on here. By the looks of things at Virtu - at least as of the [...]
In this FOURTH of a five-part video blog series Jim Jockle, CMO of Numerix sits down with Paul Rowady, Director of Research at Alphacution to discuss the recent FinTech Revolution. They discuss how firms are gearing themselves towards a digital culture, and how companies are working to distinguish themselves in this new age. The five videos cover the following: Part 1: Paralysis by Analysis: Preparation & Analyzation for Digital Disruption Part 2: IT Outsourcing and Transformation Part 3: Revolutionizing FinTech: Looking into the World of Data Automation Part 4: Technological Implications of Cultural Transformation Part 5: Digital Noise in the FinTech Space Jim Jockle (Host): So let me go to your research. You know you suggested a little bit, there’s the differentiators in terms of maximizing our opportunity and then there’s a congested middle-of-the-pack. Transitioning, so yes you had the Fords, who arguably have done very well in that or a transitionary period of time but you also saw the Hondas and Toyotas come out of nowhere and things of [...]
In this SECOND of a five-part video blog series Jim Jockle, CMO of Numerix sits down with Paul Rowady, Director of Research at Alphacution to discuss the recent FinTech Revolution. They discuss how firms are gearing themselves towards a digital culture, and how companies are working to distinguish themselves in this new age. The five videos cover the following: Part 1: Paralysis by Analysis: Preparation & Analyzation for Digital Disruption Part 2: IT Outsourcing and Transformation Part 3: Revolutionizing Fintech: Looking into the world of Data Automation Part 4: Technological Implications of Cultural Transformation Part 5: Digital Noise in the Fintech Space Jim Jockle (Host): What is the role of outsourcing? In the sense of at the end of the day traders are paid to trade. Financial advisors are paid to give advice and on the benefit and breadth of their customer base. Banks are meant to control and manage deposits. There’s still a fundamental core business but yet technology and the risk profile of all these institutions is the [...]
If you happen to hear the drumbeat of these things called "operational analytics" getting louder, then you just may be dialed in to the subtle downstream impacts of some of today's most common headlines related to financial enterprise transformation. For instance, the fintech revolution we are living through - with all its new-fangled and often overly-hyped gadgetry - is really about harnessing the opportunity for unprecedented process efficiencies. But, while it is a soothing distraction to daydream about deploying new digital tools during the ongoing regulatory hurricane, the economic impact that they will have on the FSI landscape is barely going to move the needle anytime soon. Of course, there are exceptions to this broad brush stroke: The impact of evolving IT infrastructure solutions from Infrastructure-as-a-Service (IaaS) to software defined networks (SDNs) to any number of other high-performance compute and storage tools are already sufficiently mature to be making a major impact on architectures and technology buying patterns. A similar statement could be made about open source big data tools such [...]