Paul

About Paul Rowady

Paul Rowady is the Director of Research for Alphacution Research Conservatory, an institutional research and strategic advisory platform uniquely focused on modeling and benchmarking the impacts of technology on global financial markets and the businesses of trading and asset management. Based on an expanding research library focused on the modeling of specific market actors, composited industry segments, and key thematic drivers, the Alphacution platform is specifically designed to deliver data-driven and quantitatively based intelligence to a forward-thinking network of market participants and their stakeholders. Paul is a 35-year veteran of the proprietary, quantitative and derivatives trading arenas. Contact: feedback@alphacution.com.

#DigitalMythology: The Searing Truth of Context

The primary goals of this ongoing series of research are to quantify - in increasing detail - what the members of the financial services industry (FSI) ecosystem spend on technology (including hardware, software, data and IT human capital) – which is sometimes referred to as (enterprise) total cost of ownership (TCO); develop benchmarks and analytics that help describe the absolute and relative nature of these spending patterns; and then, use the findings to confirm, deny, expand the prevailing (or introduce new) narratives in the space. The first phase of modeling has focused on the largest IT solution buyers, a selection of over 50 of the world’s largest banks – plus a few others whose purpose, for now, is to help us place this initial sample of FSI players in proper context. (More on this shortly.) Subsequent phases of modeling will incrementally build upon this foundation with the addition of other constituencies in the FSI ecosystem until a comprehensive view is maximized. With this as a backdrop, we have been focusing on [...]

By |2020-10-05T21:04:45-04:00December 6th, 2015|Open|
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#DigitalFrontier: Guiding Lights for the Analog Galaxy

Before everyone heads off to worship at the Altar of Tryptophan for a few days, I wanted to share some updated analysis: (I promise to keep it as short as possible, but unfortunately no less dense than usual.) In a recent post, #Technical Leverage: Can You Defy Your Scale?, I added Google’s (and Virtu Financial’s) RPE (revenue per employee) analytics to our core assembly of the 51 largest global banks. Given Google’s stand-out RPE of US$ 1.23 million (2014), I developed a hypothesis that this was a common theme among similar Dot.com / Internet-related leaders; that perhaps there was a pattern that would help us better describe and understand the nature of the digital revolution. Before we go to the visual, it is often the case in the search for meaning in new mega-drivers that there is a refinement of language and labeling exercise that needs to take place. After all, if we are too cavalier about the definition of new mega-drivers – if “digital” is in fact new at [...]

By |2020-10-05T21:04:38-04:00November 24th, 2015|Open|
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#TechnicalVirtuosity: The Player is the Special Sauce

Once upon a time, a few clicks back into my youth from now, I fancied myself a fairly decent piano player. That illusion came to an abrupt demise when I met Fred Johnson. On the surface, Fred was as milquetoast-Midwestern as they come. You might have expected hay to fly out of his mouth when he spoke. But, that assessment would have been seriously flawed, as I soon learned. It turns outs that Fred was blessed with perfect pitch, had any number of the very long and complex Rachmaninoff and Prokofiev concertos perfectly lodged in memory, and the speed of someone afflicted with the gift of 25 fingers – and all by the 9th grade. He was a quintessential virtuoso as far as I was concerned. What Fred produced at the same piano and with a quick glance at the same sheet music as I had been laboring over for weeks were two entirely different definitions of music. In short, I would need to discover my own virtuosity away from [...]

By |2020-10-05T21:04:29-04:00November 19th, 2015|Open|
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#Technical Leverage: Can You Defy Your Scale?

If you believe the latest bromides, “IT strategy is business strategy”, then the success of any business is predicated on the deployment of technology – which includes the perpetual coordination of hardware, software, data and IT-related personnel (or human capital). Alphacution has applied this hypothesis to the financial services industry (FSI), first by modeling the technology-related spending of 51 of the largest global banks – arguably among the biggest buyers of technology in the FSI ecosystem – and then generating a series of benchmarks, analytics (many of which fall under the label, “T-Greeks”), visuals and narratives to describe how each market actor is performing in that ecosystem. Off the back of this first version of the Alphacution Composite Model, regional and global industry patterns also emerge, in addition to entity-specific metrics. Focus on Revenue per Employee One of the most fascinating pictures we have been able to generate in these early stages of the modeling is a normalized ranking of the sample banks by revenue per employee (RPE), where “employee” [...]

By |2020-10-05T21:04:20-04:00November 12th, 2015|Open|
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#DigitalTransformation: (More) Clues to Shifting Financial Services Technology (Part II)

The following is Part 2 in the series “#DigitalTransformation: Clues to Shifting FinTech” published on November 2, 2015. Digital crumbs don’t discriminate. They illuminate everything. True to this, and despite intense focus on cloud-based offerings, infrastructure-as-a-service (IaaS) and other managed services solutions, the digital transformation in the financial services industry (FSI) is by no means confined to hardware. Software development in FSI is in the midst of its own revolution, as well. In either case, and by my my estimation, overall fintech is now entering its third year of “white-hotness.” As a reminder, in Part 1 of this commentary, we highlighted growing evidence of the shift from capital expenditures (“capex”) to operating expenses (“opex”) for hardware and other infrastructure. In an upcoming post, we will dig a bit deeper into this theme by showcasing what the previously announced multi-billion dollar outsourcing deal between Deutsche Bank and Hewlett Packard (February 24, 2015) means for IaaS and other managed services adoption in FSI generally and for large global banks in specific – [...]

By |2020-10-05T21:03:54-04:00November 11th, 2015|Open|
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#DigitalMantra: The Key to Operational Agility

Clear your mind and repeat after me: “I am a revenue center.” Again: “I am a revenue center.” Again: “I am a revenue center.” Practice this mantra until it influences your perspective on your own work. I actually tried this stunt at the end of a presentation to an audience of data specialists and related personnel at a recent FIMA Canada conference. Though there appeared to be a quiet skepticism at such an unorthodox request from the stage, a surprisingly large portion of the group seemed to get the liberating nature of the exercise. A few actually participated in the audible! Others, we can only guess, participated in their heads. Either method is fine. In any case, the genesis for the need for such a realignment of perspective comes from the fact that many of us have been “sold” the idea (by management) that we are part of the cost structure; that we are part of the organizational algorithm where only expenses exist. However, in order for optimal operational agility [...]

By |2020-10-05T21:03:46-04:00November 10th, 2015|Open|
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#DigitalTransformation: Clues to Shifting Financial Services Technology (Part I)

Digital crumbs are everywhere. Like the fabled trail left behind for others to follow and discover, there are fascinating clues to be harvested from increasingly abundant data. Yes, the fast-streaming and big data versions of these digital crumbs offer untold clues and patterns – but only seen after applying the latest apparatus to the chore. There are also amazing clues to be discovered by picking up one crumb at a time (often by hand) - and then assembling that collection into a vivid prototypical picture. One of the most potent forms of data innovation comes from such manual assembly of these “crumbs” followed by process refinement, technology deployment, iteration of these steps and ultimately increasing levels of automation. It’s not the glamorous end of the data innovation assembly line, but it is absolutely necessary to get there. (Thank the folks in your enterprise data management group if you like the flow of analytics to your desktop or mobile device.) Anyway, here’s a potent case in point: Some of these so-called [...]

By |2020-10-05T21:03:32-04:00November 2nd, 2015|Open|
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#TechnologyVolatility (T-VOL)

According to Al Pacino, as Coach Tony D’Amato in the movie, Any Given Sunday, “this is a game of inches - the margin for error is so small - and the inches we need are all around us.” With this in mind, it turns out that measuring technology spending in detail represents some of those so-called inches. Personally, I have found such an analysis to yield really incredible and exciting insights – representing more than just a few of those inches. Our TPE Dispersion Analytic – known as T-VOL™ – is one of the better specimen to support such a claim, at least so far. First, let me detangle some of the jargon so that you can see how (potentially) cool and useful this analytic could be: We developed individual models of the largest banks in the world – currently numbering 51 – capturing financial and operational data over the pre- and post-GFC period, 2005 – 2014. For each bank, combining estimated non-human capital (NHC) technology spending with reported headcount [...]

By |2020-10-05T21:03:23-04:00October 27th, 2015|Open|
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#humanlatency

Though you may have fully gorged yourself on tales of latency over the past few years, I’m here to tell you that that overall story is far from over. Reason being, there is more than one form of latency – and the value (or cost – depending on your perspective) of at least one of the other types of latency will make the first narrative – the super-sexy knocking-on-the-door-of-the-speed-of-light version – seem like the Leda moon orbiting Jupiter. This is where human latency enters the vernacular. From where I sit – and though the nuances can be hotly debated beyond this short essay - there are actually three primary forms of latency - and a couple hybrid versions of those. These primary forms include “network / proximity latency”, “compute latency”, and “collaboration latency”. (Of course, the technology arms race of the past decade dealt almost exclusively with minimizing network / proximity latency.) Each of these general forms is a mix of native technical and human latencies, as follows (see Exhibit 1): With this rudimentary [...]

By |2020-10-05T21:03:14-04:00October 22nd, 2015|Open|
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#GlobalTCO

Ever wonder what the global financial services ecosystem spends on technology? I have - obsessively. The size and shifts of this market – and the tapestry of moving parts within it – is extremely valuable intelligence for all players in the FSI ecosystem. Moreover, with the intense focus in recent years on topics like “XaaS”, clouds, solid state memory, Hadoop clusters and so many other symbols of fintech innovation it is abundantly clear that this is the one puzzle that needs to be solved. Problem is: crossing the bridge from here to there while keeping a credible process intact is sufficiently complicated to dissuade most sane contenders from attempting the feat. Of course, that is unless you are someone who thrives on solving insanely complex puzzles that defy common temperaments. Simply put: It all starts by following the money, which by the way is also a decent proxy for following the data. My Uncle Lewis was a stockbroker in Detroit for most of his 89 years. He was the kind of [...]

By |2020-10-05T21:03:02-04:00October 22nd, 2015|Open|
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