With U.S. trade policy shifts fuelling intense market volatility, many FX trading firms are enjoying a surge in trading volumes. But behind the scenes, there’s also a fair bit of nail-biting. Spiking activity and unpredictable price swings—reminiscent of the COVID-era chaos—are once again testing the resilience of trading infrastructure.
In the highly dynamic world of electronic foreign exchange trading where geopolitical flare-ups and economic surprises can spark seismic price moves, technology isn’t just an enabler, it’s a critical strategic asset. However, firms must juggle performance, resilience, and budget constraints, all while striving to stand out in a highly competitive market.
This raises a pivotal question: should firms build their own trading infrastructures – which may need to include algo execution functionality – or tap into the capabilities of third-party solutions? Historically, this has been a debate centred on control, cost, and competitive edge. But as technology evolves and managed infrastructure matures, the lines between what’s worth building versus buying are being redrawn.
The build vs. buy debate: reframed
Traditionally, building your own system offered maximum control over performance, fine-tuning every layer, from execution logic to latency optimisation. This was especially attractive to large sell-side banks and HFT firms, hunting every microsecond of edge.
On the flip side, buying pre-built solutions offered speed (time-to-market), reduced project risk, and access to external expertise. Smaller firms, constrained by budget and specific expertise, often leaned on white-labelled platforms or specialist vendors to stay competitive.
But the landscape has shifted. It’s no longer just about speed vs. control because new technologies and operating models have redefined what’s possible.
What’s changing? The tech evolution behind the shift
The advent of next-generation technologies is transforming how firms approach this decision. Cloud computing and high-performance managed colocation in FX hubs like LD4 and NY4 are reducing barriers to entry. Firms can now scale infrastructure as needed, without the burden of upfront capital investment. This “infrastructure-as-a-service” model is levelling the playing field, enabling firms of all sizes to tap into low-latency, scalable environments and execute sophisticated trading strategies under a flexible opex model that better aligns costs with revenues.
API-driven modular platforms are also changing the game. Firms can now more easily plug in specialist tools (such as execution algorithms, pricing engines, or liquidity modules) taking a modular, best of breed approach leveraging in-house and third-party applications. This approach frees organisations from committing to a single monolithic system and frees internal developer and quant teams to focus on delivering genuine competitive advantage, leveraging third parties for critical but non-differentiating components.
For regional or mid-sized players, this approach can be a game-changer. With smaller budgets and limited quant expertise, they can still deploy cutting-edge tools via open APIs, integrating third-party algos and tools without the overhead of a full in-house build.
The role of AI and ML: hype or help?
Artificial Intelligence (AI) and Machine Learning (ML) are becoming increasingly embedded in FX trading workflows, from analytic models to execution algos. But the reality is these technologies demand deep datasets, serious computational power, and highly specialised talent.
For many firms, building AI capabilities from scratch is a daunting task and may not be feasible for many. A better option? Partnering with vendors already investing heavily in AI, allowing firms to gain early access to capabilities they wouldn’t otherwise develop in-house.
This isn’t just about efficiency it’s about survival. With AI poised to become the next battleground for execution quality, those who don’t adopt will likely fall behind.
Regulatory pressure adds complexity
It’s hard to ignore regulatory trends in the context of capital markets. The recently implemented Digital Operational Resilience Act (DORA) in the EU has raised the bar on how firms handle operational risk, cyber resilience, and third-party oversight.
While building in-house systems may provide more direct control over compliance and reporting structures, vendors are rapidly enhancing their platforms to meet these demands. In many cases, third-party providers have cross-jurisdictional insight and specialist compliance teams that allow them to adapt faster than internal development cycles allow. They also have the advantage of working with multiple customers, sitting in the centre of an industry feedback loop.
So, while regulation might initially seem like a reason to build, it may actually strengthen the case for selectively outsourcing and leveraging the investment and expertise of third parties.
Making the call: What to build and what to buy?
There’s no one-size-fits-all solution. But here are four key areas firms should assess when defining their strategy:
1. Differentiation potential
- Build what sets you apart, custom algos, unique execution logic, proprietary data models, and other capabilities that genuinely help you stand out from your peers.
- Buy common capabilities, middleware, risk systems, back-testing and analytics tools or where vendors may be ahead of the curve (like in AI).
2. Cost and scalability
- Building can deliver to your exact needs but can also be expensive and risky. Upfront investment, talent acquisition, and long development cycles can strain even large budgets.
- Buying potentially offers more predictable opex and scalable infrastructure, especially with SaaS and cloud models that grow with your needs.
3. Compliance and resilience
- In-house systems can offer more control over data and faster adaptation to regulatory changes, especially under frameworks like DORA.
- But vendors bring deep regulatory know-how from serving multiple clients, often easing the burden on internal teams and speeding compliance delivery.
4. Integration and staff continuity
- Legacy in-house stacks can become brittle over time, especially if documentation is lacking or staff turnover is high.
- Vendor platforms, built with modern, API-first principles, are easier to integrate and maintain and vendors usually have deeper talent pools to support ongoing operations.
The rise of the hybrid model
As the market evolves, so too does the approach to architecture. Increasingly, firms are blending in-house IP with best-of-breed vendor tools. The hybrid model allows for innovation where it counts and efficiency everywhere else.
For example, large institutions may pair proprietary quant strategies with vendor UI layers or algo deployment frameworks to reduce time-to-market and gain advantage. While a smaller, regional bank might use hosted infrastructure and third-party algos to deliver its trading stack, focusing on local expertise and client relationships to create differentiation.
All firms regardless of size face common constraints: limited resources, overloaded tech teams, and growing regulatory demands. While some firms are committed to building tech, many are realizing that they can be more efficient and agile by focusing internal efforts on what makes them stand out and relying on trusted partners for everything else.
Looking ahead: The next evolution in FX trading architecture
The FX industry isn’t done evolving, far from it. The next generation of FX trading infrastructure will likely be modular, AI-enhanced, and seamlessly blend in-house IP with best-in-class third party technology. Execution decisions will be data-driven and automated. Platform architectures will need to support both human and machine workflows seamlessly.
In this future, firms that intelligently navigate the build-vs-buy continuum will be the ones that thrive. Those who try to build everything risk falling behind; those who rely too heavily on third parties may struggle to differentiate. The winners will strike a balance by building proprietary tech where it creates advantage and embracing vendor innovation where it accelerates time to value.
In short, building and buying aren’t opposites anymore. They’re two parts of a smarter, more strategic whole.
