According to Aite Group’s data and analytics partner, Alphacution, technical and human capital leverage benchmarks can be developed to represent a framework with numerous practical applications for all asset managers.
Boston, April 25, 2018 — Understanding patterns in firms’ technology consumption offers unique insights into shifts in both business strategy and operational efficiencies. But the main challenge in discovering technology consumption for the asset management universe is that these firms are mostly private, if not highly secretive; therefore, accessing the right data presents some challenges. Alphacution’s latest report, Estimating Asset Manager Technology Spending: The Context Machine, examines what asset managers are spending on technology and the relation that those consumption patterns have with the scaling of headcount, assets under management (AUM), and strategy selection.
“Alphacution believes that this research is a dramatic first step toward extending its techno-operational benchmarking framework to the global asset management universe,” explains Paul Rowady, director of research for Alphacution. “How strong the empirical context is from this initial data set—and the potential to deliver navigational intelligence to asset managers, hedge funds, and their solution partners—is what we begin to expose here,” he adds.
“While Alphacution continues to work toward building a comprehensive framework for estimating IT spending trends across the financial services industry, its most recent foray into the asset management market provides glimpses of something that could have a significant impact within capital markets,” says Sang Lee, managing partner at Aite Group.
This new report, authored by Alphacution’s Paul Rowady and edited by Aite Group’s Sang Lee, identifies an alternative path to the estimation of technology spending for asset managers by asking a different question: How do asset managers scale? Aite Group’s data and analytics partner, Alphacution Research Conservatory LLC, is the first digitally oriented research and strategic advisory platform uniquely focused on 360-degree modeling, measuring, and benchmarking for technology spending patterns, along with the operational impacts of those investment decisions, in and for the global financial services industry (FSI). The data set for this study is based on the modeling of three primary factors—technology spending, AUM, and headcount—for 158 asset managers: 60 public companies, which include all three factors over a 12-year period ending 2016, and 98 private companies, which include two factors—AUM and headcount—over a five-year period ending 2016.
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About Aite Group:
Aite Group is a global research and advisory firm delivering comprehensive, actionable advice on business, technology, and regulatory issues and their impact on the financial services industry. With expertise in banking, payments, insurance, wealth management, and the capital markets, we guide financial institutions, technology providers, and consulting firms worldwide. We partner with our clients, revealing their blind spots and delivering insights to make their businesses smarter and stronger. Visit us on the web and connect with us on Twitter and LinkedIn.
About Alphacution Research Conservatory LLC:
Alphacution is the first digitally oriented research and strategic advisory platform uniquely focused on 360-degree modeling, measuring, and benchmarking for technology spending patterns, and the operational impacts of those investment decisions, in and for the FSI. Founded by market veteran Paul Rowady, the Alphacution platform is specifically designed to deliver data-driven and navigational intelligence for financial information, analytics, and techno-operational themes related to the FSI to an institutional client network by leveraging multimodal communication and other digital-era tools, technologies, and methods in the development and delivery of its products and services. More information can be found at www.alphacution.com. Please send inquiries to firstname.lastname@example.org and follow @alphacution.
Additional information about this report:
To learn more about this study, there are a couple easy options that are only a click away:
- Set aside some time to watch Alphacution Riffs Ep 4 wherein we walk through the foundational hypothesis; key highlights; an extraordinary case study involving Citadel, Millennium Management, Point72 and Vanguard (teaser); and, the strategy behind the release of this groundbreaking study, The Context Machine…
2) Next, you can easily download a comprehensive executive summary of the study, below.
How to Purchase
Terms of Purchase
Terms of purchase are identical from either party, Alphacution or Aite Group.
An enterprise license for this report also includes a credit for the total purchase price which can be used as a discount for Alphacution’s annual enterprise subscription, equivalent customized engagements, or some combination thereof valued at $50,000 or more for a period ending one year after the re-launch date of our content management platform, which is currently estimated to be a period ending 3rd quarter 2019.
Annual Subscription and Upcoming Research
The discount credit on this study purchase is extended into late 2019 because annual enterprise subscriptions to Alphacution’s research archive have been temporarily suspended while we execute on a substantial content management feature upgrade. Clients may still access Alphacution’s core studies via its feature page at Aite Group and/or ad hoc arrangements with Alphacution, including custom engagements.
In the interim, and over the course of the next 12-18 months, the following studies are scheduled on our research roadmap; ultimately becoming accessible via single report purchase, annual subscription, or as an embedded feature of a customized engagement:
- Enterprise IT Solutions and “Big FinTech” Study (Initial): Focus on the largest solution providers related to global financial services, including 20 Enterprise IT firms and 30 “Big FinTech” firms. Key objectives of this study are to compare vendor revenue patterns with technology buyer expense patterns in support of further segmenting tech buyer spending beyond the current status, which is enterprise-level hardware, software and IT human capital (for banks) – and into workflow categories, like front-, middle- and back-office and/or task categories, like research / signal generation, execution, portfolio management, risk, and post-trade processing.
- Global Bank Technology Spending Study (1st Update): Focus on modeling, measuring and benchmarking enterprise technology spending patterns for the largest banks – with segmentation into hardware, software and IT human capital components; expanding Alphacution’s existing bank composite model from 60 to as many as 80 individual bank models (which means modeling further into the retail bank arena); and, beginning to apply the “human capital leverage” concept and the potential to benchmark levels of automation that was first used in the asset manager sector modeling.
- Asset Manager Technology Spending Study (1st Update): Focus on expanding the roster of asset managers and hedge funds from the current US$10 billion AUM minimum threshold down to a US$1 – 5 billion AUM threshold; and, applying the recommendations for further analysis from the initial asset manager technology spending study, each of which relates to the application of additional segmentation factors that have potential to improve the estimation accuracy and benchmarking potential of the existing framework.
- Global Exchange Technology Spending Study (Initial): Focus on modeling, measuring and benchmarking technology spending patterns among a global roster of approximately 25 exchanges, including updates to Alphacution’s existing modeling on market data / non-market data themes.
- Note: Core studies are supported by premium-access episodes of Alphacution Riffs (including video tutorials, select case studies); and, detailed exhibits from related modeling. Furthermore, the modeling components, timing and chronology of the aforementioned studies – as well as features and pricing of annual subscriptions – are contingent upon ongoing client, stakeholder, data availability, new data discovery and other drivers, and therefore, are subject to periodic modification without notice.
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