Build vs buy is no longer a binary question

For years, asset managers treated technology strategy as a binary decision: build for control, or buy for scale. That framing no longer fits the market. The variables have changed – cost structures, AI, regulatory pressure, data demands, and the pace of market evolution are forcing firms to revisit assumptions that may have been formed 10 or 15 years ago.

For COOs, CTOs, and senior decision-makers, the sharper question is not "should we build or buy?" It is "where does ownership actually create advantage – and where does it quietly consume capacity, capital, and focus?"

The priority is no longer to own every layer of the technology stack, but to identify where proprietary control creates genuine advantage – and where standardized, resilient infrastructure can free capital, capacity, and talent for higher-value work.

The economics of “build” have changed

Investment infrastructure is under pressure from every angle. Regulatory acceleration – from T+1 to increasingly complex reporting requirements – has raised the operational bar. Compliance is a continuous element, not a one-off build.

At the same time, the data environment has exploded. Real-time pricing, sustainability, private markets, and alternative datasets are stretching legacy architectures beyond what they were designed to handle. And then there is cost. Engineering talent is scarce and expensive. When firms spend a large proportion of their tech budgets maintaining legacy systems, the issue isn’t just technical debt – it’s lost innovation.

Every hour spent maintaining infrastructure is an hour not spent building differentiated capabilities. "The key takeaway is that capacity is finite. Maintaining plumbing – especially for commoditized functions – may not be the best use of that capacity", says Michael Campos, Head of U.S. Asset Managers, Aladdin Business Development.

The real cost of “build” shows up at scale

The challenge with internal systems is not the initial build – it’s operating them over time. Firms shouldn’t be asking "can we build it?" They should ask "can we sustainably operate and evolve it over the next 10 or 20 years?"

Some of the real costs include:

• Integration tax: Every new asset class, workflow, or data source requires new integration work. Complexity compounds.
• Resiliency burden: Uptime, disaster recovery, and cybersecurity are full-time disciplines – not side projects.
• Key-person risk: Critical systems often rely on a handful of architects, creating unhedged operational exposure.
• Opportunity cost: Engineers maintaining core infrastructure are not building alpha-generating tools.

AI changes the equation – and raises the stakes

AI is dramatically lowering the barrier to building software – teams can spin up tools, dashboards, and workflows faster than ever. But that’s only half the story.

"AI is only as good as the underlying data. If your data isn’t reconciled across systems, if you don’t have a single system of record, then you can’t trust the output," according to Alisha Sewdass, Head of Americas Solutions Engineering, Aladdin. If every team can create tools, who ensures they all reference the same positions, cash balances, exposures, and risk data? A dashboard built in hours is useful, but can it pull from a reconciled source of truth? Maintain audit trails? Perform under stress?

This is the paradox: AI accelerates application development but increases the premium on a governed foundation. The more tools a firm builds, the more critical consistency, control, and data integrity become.

The shift: from build vs buy to build on top

The emerging model is not either/or; it is hybrid: buy the foundation, build the edge.

Leading firms are converging on a clear principle: outsource commodity infrastructure, own proprietary differentiation. They buy the data foundations, lifecycle processing, compliance engines, resiliency, and cloud infrastructure; then build research models, alpha signals, analytics, and portfolio construction IP.

"You can leverage that backbone infrastructure – foundational data and foundational workflows integrated across portfolio management, trading, and operations – and then build on top of that, knowing you have the core infrastructure and governance aligning those workflows," Sewdass says.

“Buy” has been redefined

Historically, buying meant compromise: closed systems, rigid workflows, and limited flexibility. But today, modern platforms are open and extensible because APIs, event-driven architectures, and real-time data enable firms to build on top of a shared foundation – not around it.

“From an infrastructure perspective, that means robust APIs that manage the entire lifecycle of a transaction. If clients want to build their own rebalancing tools or optimizers, they should be able to do that – but using the same clean data and the same system of record,” suggests Sewdass.

The key question is no longer "will this replace our differentiation?" It is: "Can our proprietary models generate custom risk factors that seamlessly feed into portfolio construction, risk management, and order modeling through governed APIs?" When the answer is yes, "buy" becomes an enabler of innovation – not a constraint.

What this means for asset managers

Asset managers require a more disciplined view of what belongs inside the firm. If a capability does not directly contribute to alpha, client outcomes, or competitive differentiation, owning it is unlikely to create value.

In an AI-driven environment, this becomes even more critical. As building becomes easier, the challenge shifts to control – ensuring consistency, governance, and a single source of truth across an expanding set of tools. The stronger the foundation, the more effectively firms can innovate on top of it.

Ultimately, the constraint is focus. Engineering capacity is finite, and the firms that succeed will be those that deploy it deliberately – concentrating on what differentiates them, and stepping back from what does not.

Five questions to ask now

1. How much of our engineering spend goes to maintenance vs. differentiation?
2. If we had to re-platform in three years, what would we still choose to own?
3. Are we building AI on a governed data foundation – or on fragmentation?
4. Where do we have key-person risk in critical systems?
5. Are we making a 2026 decision with a 2015 framework?

To learn why build vs buy is no longer the right question, watch our webinar, where industry experts explore how asset managers are moving beyond the debate to scale more efficiently.

Build vs Buy: How Asset Managers Are Rethinking Key Decisions Today with Alisha Sewdass, Head of Americas Solutions Engineering, Aladdin, Clark Shafer, Partner, Asset and Wealth Management Consulting, North America, Alpha FMC, and Michael Campos, Head of U.S. Asset Managers, Aladdin Business Development.