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#PassingTheBuck: DB-HPE Tech Outsourcing Deal, 1-Year Anniversary

Squeezing more performance from less costly technology footprints is a perpetual imperative for all businesses in the digital age. Unlike the latest – and ongoing – turbulence on the surface of the global markets seas, something slower, somewhat mysterious and much more evolutionary is going on down in the deep. One might argue that the largest global banks head the list of those businesses that are among the most in need of “more-for-less” transformation. As a result, monitoring the impact of events such as the Deutsche Bank – Hewlett Packard Enterprises information technology outsourcing (ITO) deal is of such importance. Alphacution has developed a detailed and quantitative case study to illustrate the bank- and business division-specific - impacts of this arrangement as well as the implications for improved monitoring of the transformations of other large entities in the financial services industry (FSI) ecosystem. First, some quick background:  On February 24, 2015, Deutsche Bank (DB) and Hewlett-Packard (since re-configured as Hewlett Packard Enterprises – or HPE) announced a 10-year,”multibillion dollar” agreement [...]

By |2020-10-05T21:05:12-04:00March 2nd, 2016|Open|
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#CrowdedOut: Banks’ Technology Spending Paradox

They really don’t have a choice here. And yet, in this “everything is customizable and personalize-able” world in which we now live, we have grown to expect that there is always an infinite spectrum of choices available. Not so much when it comes to banks’ spending on technical infrastructure. It turns out that internally-developed software costs (which we believe includes both proprietary and consultant-developed software) are the fastest growing component of our technology total cost of ownership (TCO) framework, which includes hardware, software, data and human capital. Of the 50+ large global banks that we have modeled so far, most of them throw off a similar picture as the one in the sample exhibit below of a large APAC bank. Here the accumulated net carry value of software is being driven almost exclusively by spending on internally-generated software – and far outstripping the growth in spending on computer hardware / equipment. Furthermore, it doesn’t matter if the bank is in the Americas, Europe, Asia or anywhere in between. Most of [...]

By |2020-10-05T21:05:04-04:00February 11th, 2016|Open|
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By |2020-12-24T18:20:43-05:00January 1st, 2016|Open|
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Yellen and Me: The Catalyst Behind the Rate Decision

< This is a test. This station is conducting a test of the Emergency Broadcast System. This is only a test.> I had been in this room before. It was the early post-Dodd Frank days. Maybe February 2012. I had authored a study on the impacts of new regulations on collateral and initial margin requirements for OTC derivatives (OTCDs). The study had been commissioned and was being promoted by the World Federation of Exchanges (WFE). Largely as a result of my global initial margin estimate of US$ 2 trillion for OTCDs, it had made a big splash. On the back of this, the event invites and media came knocking. My friend, John McPartland – “McP” to those who knew him longer than 15 minutes – invited me to present at a monthly luncheon for Chicago financial muckety-mucks. Now, it was good to be back. For this night’s event - set at the corner of LaSalle and Jackson in the main gathering space on the 2nd floor of the Chicago Fed [...]

By |2020-10-05T21:04:55-04:00December 15th, 2015|Open|
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#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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