Summary
Institutional asset managers are increasingly buying investment data foundations instead of finished applications. API-first, headless architecture with native model context protocol (MCP) integration and cloud architecture enables horizontal scaling with omnichannel delivery. This lets firms retain proven processing, accounting, and operational workflows while building their own interfaces, AI experiences, and reporting. The result is greater flexibility, stronger data ownership, and less dependence on vendor roadmaps.
Technology fatigue is real inside asset management shops now. In a perfect world, firms would build the best technology stack possible, close the book on digital transformation, and then go about their lives driving alpha. Many chief technology officers (CTOs) who spent the last decade consolidating onto all-in-one platforms now demand foundation architecture that can be decoupled from the UI to deliver a truly bespoke application to their users; this includes selective adoption of platform components and the ability to bring their own interfaces, all on their terms.
In the last few years, as structural complexity and associated technological complexity increased, firms had to expand their headcounts, increasing product specialists by 60% and operations professionals by 30% (2020 to 2024).i CTOs can no longer lean on rigid platform models that lock them into a single vendor, add disruption, come with a heavy integration burden, or restrict data ownership. All-in-one platforms and a stack of connected SaaS applications designed to solve one use case don’t usually integrate well with other systems.
It’s a costly endeavor to maintain legacy systems along with numerous unintegrated solutions for functions like accounting, performance analytics, and reporting. If you’re already paying for three separate applications, adding a fourth takes months to integrate and operationalize, when what you need is something that displaces two or three existing cost centers and layers on without a rebuild.
Headless architecture allows developers to create multiple front ends for various formats at once and plug into third-party systems. It represents a specific type of front-end user interface that is decoupled from underlying, back-end business and application logic. This happens through APIs to let front-, middle-, and back-office tools plug directly into financial datasets without a monolithic software constraint.ii MCP integrations and AI querying have created a new way for business users to interact with back-end infrastructure. Users benefit from agentic workflows and intelligent query responses without directly interacting with datasets, models, or even workflows, thus simplifying the entire modern data access paradigm.
In fact, API-based investment operations mean that firms don't ever have to interact with the application’s online UI. Instead, they interact with the behind-the-scenes shell of the databases, data models, and operational workflows.
AI has significantly increased the ability for technical and non-technical users to build their own visualizations, reports, and applications. Clients no longer want this concept of everything outsourced, everything SaaS, because that means that the data lives somewhere else, and they’re locked into multiple UIs. That’s why we favor a headless investment platform/bring-your-own-interface for buy-side firms.
In enterprise SaaS, building your own components has become more feasible because with AI programming tools, fewer development resources are now required. Firms can choose their own UI journey of how they want to consume information, customize delivery mechanics, create bespoke workflows, and deploy configurable applications on top of the foundations necessary. Users get a say in how they display information and how they report it. Now they can BYOI within a scalable operating model.
Using headless architecture, firms get processing power, scalability, a predefined ontology of models, along with standardized processing operations. Firms buy the data foundation rather than the finished application, giving firms a unified, authoritative source for portfolio data integration, accessible via API.
Firms are frustrated by having to expend resources in support to compensate for integration shortcomings. Subsequently, they get something only resembling consolidated data, integrated workflows, and live portfolio visibility. Many buy-side firms have connected systems but lack a true total portfolio view.
Because closed architecture applications are locked to their original assumptions, they often fail to keep up with the latest advancements over a decade or more. A headless approach allows firms to scale and adapt as their business grows.
Otherwise, the tech team would have to try to rewrite the foundation at the bottom to add new tools on top. They can’t do that easily because so many clients are subscribed to the legacy model that it would completely disrupt their existing client base.
"Many asset managers continue to operate on aging infrastructure that is expensive to maintain, and the absence of well-integrated systems has made supporting core operations costlier and stymied innovation with newer technologies like generative AI. The expanding operating model sprawl within many asset managers’ organizations has compounded cost increases." — McKinsey on Investing, McKinsey & Co., November 2025iii
The open, headless architecture and API-based infrastructure make smooth integrations possible. Together, these constitute what we call the ecosystem model. The data lives somewhere else when using a closed application layer.
The ecosystem model is all about interoperability, shared data models, and extensibility, the ability to add components easily. Most systems are extensible only in certain ways: A given system may simplify adding new tools that use the data already in the system, but integrating new types of data to that same system may be onerous.iv
Our engineers have had extensibility in mind for institutional asset management technology from the beginning. Better still, the future of investment operating models lies in composable architecture, in which you can expand the tech stack and compose (rearrange) an operating model from interchangeable modules.
The extensible, composable ecosystem model combines platforms, partners, and custom development without creating integration sprawl. The ecosystem model’s open architecture also determines who owns the data, and that shift matters as much as the flexibility. With unassailable data ownership comes data portability. Firms can adopt new asset classes, vendors, and strategies without re-platforming.
"At every level of the business technology stack, composable modularity has emerged as the foundational architecture for continuous access to adaptive change. Businesses rely on it to achieve sustainable business resilience and growth." — Composable Modularity Shapes the New Digital Foundation, Gartner, January 2024v
Firms hired people to do what their systems couldn’t, but on a closed stack, headcount numbers become a tax on broken infrastructure. The foundation itself is a constraint, and the firms positioned to move fastest are the ones that already own their data and can reach it via API. The ones still negotiating roadmap timelines with vendors will wait a long time.
If you’re still ripping, replacing, and building workarounds, you already know the current model isn’t working. Fix the foundation now or keep adding headcount to compensate for it.
Bernie Cabada
As Vice President of Presales Consultants at Arcesium, Bernardo leads in showcasing the company's cutting-edge capabilities through executive-level engagements, delivering compelling presentations, technical demonstrations, and proof-of-concepts. His proficiency extends across crucial areas of middle and back-office investment operations, with a particular emphasis on data governance and enterprise data management for investment managers and asset owners.
Sources:
i McKinsey & Co., September 18, 2025. https://www.mckinsey.de/industries/financial-services/our-insights/asset-management-2025-the-great-convergence
ii TechTarget, February 17, 2021. https://www.techtarget.com/searchapparchitecture/tip/An-overview-of-headless-architecture-design
iii McKinsey & Co., November 2025. https://www.mckinsey.com/~/media/mckinsey/industries/private%20equity%20and%20principal%20investors/our%20insights/mckinsey%20on%20investing%20issue%2011/mck259165%20movest%20compendium%202025_v8.pdf
iv ScienceDirect, 2026. https://www.sciencedirect.com/topics/computer-science/extensibility
v Gartner, January 8, 2024. https://www.gartner.com/en/documents/5083331
No spam. Just the latest releases and tips, interesting articles, and exclusive interviews in your inbox every week.
