What changes have you seen in FX algo use on FXGO and what is driving that demand?
Interestingly, we’re seeing the growth in algo trading on FXGO across a range of client types including asset managers, hedge funds, and regional banks, and across instruments that would have been considered too complex or illiquid for algo execution not long ago. Buy-side desks are managing more complexity with more currencies, more instruments, more regulatory obligations, except with the same or fewer people. Algos offer the consistency, repeatability, and governance that manual execution simply can’t deliver at scale. That combination of operational pressure and improved platform capability is what’s driving demand.
What factors are currently influencing the rate of algo growth in FX?
Three things are converging across the market.
First, the underlying infrastructure has matured: more venues are offering regulated electronic execution, liquidity in instruments like NDFs has deepened considerably, and the technology underpinning price streaming and order management has become significantly more robust. That creates the conditions for algo execution to work in markets where it previously couldn’t. On FXGO, more than 250 banks stream spot liquidity across 100+ currency pairs, alongside 16 banks providing streaming NDF liquidity across Asian and Latin American currencies and a growing number of providers streaming swaps. Using the expansion of streaming liquidity on FXGO as a proxy for the broader availability of electronic liquidity, we see a strong foundation for continued growth in algorithmic execution.
Second, instrument coverage has broadened industry-wide, with algo strategies now available across NDFs, swaps, and precious metals, allowing firms to standardise execution workflows across a much larger portion of their FX activity. On FXGO specifically, clients can now execute algorithmically across more than 190 currency pairs, including NDFs and precious metals, which means firms can standardise their execution workflows across a much broader portion of their FX activity.
Third, buy-side operating models are changing. Asset managers and hedge funds are under sustained pressure to do more with less with the same or smaller teams. Algos offer the consistency, scalability, and governance that manual execution can’t deliver at that kind of scale.
Is the rise more pronounced in particular types of algo product?
NDF algos have been a standout area, with volumes up year-on-year on FXGO. That’s a market that was widely considered too fragmented and illiquid for algo execution until relatively recently. What’s changed is a combination of better electronic liquidity, improved regulatory clarity, and a more sophisticated participant base.
APAC has been particularly strong, driven by the growth of NDF markets and a rapid shift toward electronic execution.
We’ve also seen strong demand for bulk routing to algos and the ability to route multiple orders to an algorithm simultaneously rather than one by one. This demand is particularly prevalent across asset managers, and it’s a good example of how algo innovation is increasingly being driven by client workflow needs rather than technology for its own sake. We have exciting things in development here and in basket algo support with more to be announced soon.
Are there areas where algo use can be expected to rise?
NDFs will continue to be a major growth area as liquidity deepens and more venues develop NDF-specific strategies. FX swaps and precious metals are also gaining traction as clients look to bring more of their activity into a consistent electronic workflow. An orthogonal area of growth is workflow, where clients increasingly prefer to execute portfolios or baskets of orders using a common set of parameters and execution instructions, rather than executing each order individually. This enables clients to manage larger and more complex sets of orders more efficiently while applying a consistent execution strategy across the portfolio.
Can you explain where the electronification of algos actually stands today?
Algo execution in spot FX is well established and relatively mature. Beyond spot, we’re at an earlier stage; NDFs are developing quickly, but liquidity remains uneven across currency pairs and regions. FX swaps and certainly options are further behind still. The honest picture is that electronification is progressing, but unevenly, and the pace varies significantly by instrument, region, and client type. What’s important to recognise is that electronification is not a binary state. It’s a spectrum, and most institutions are somewhere in the middle, running electronic execution for part of their flow while relying on voice for the more complex or relationship-dependent trades.
What is the automation reality gap and why should clients be aware of this?
The automation reality gap is the distance between what firms say they can automate and what they actually automate in practice. The reality is that voice and electronic execution are complementary, not competing. Large-notional trades, complex structures, and relationship-sensitive flow will remain voice-driven for the foreseeable future. The risk is that firms set unrealistic automation targets, encounter friction, and lose confidence in the process.
Our focus is on supporting clients as they trade today, while identifying the surrounding workflows where automation can deliver meaningful progress.
What does FXGO do to additionally educate and support algo users?
Beyond the platform itself, we work closely with clients to build tailored roadmaps based on their specific needs and operating models.
On the analytics side, we’ve invested in algo analytics hosting, which allows providers to deliver pre-trade and live-order performance data directly within the FXGO workflow, and we’ve integrated Bloomberg TCA so clients can compare algo execution against risk-transfer alternatives on a like-for-like basis. That gives clients a measurable, data-driven foundation for algo selection and continuous improvement.
What benefits can AI offer in improving FX workflows?
At this stage AI is primarily an efficiency tool, not yet a trading strategy. The real gains are in surfacing information faster and removing manual steps, not in generating alpha. And AI is only as good as the data underneath it. FXGO’s advantage is that we sit on one of the largest pools of real-time executable FX data in the market with more than 20,000 in over 140 countries, and ADV exceeding $900 billion. That data foundation is what makes AI tooling genuinely meaningful rather than decorative.
Are there additional applications of AI which can benefit FX algo execution?
Potential algo applications include using AI to improve liquidity and volume forecasting, dynamically adapt execution strategies to changing market conditions, optimize venue and liquidity-provider selection, and enhance transaction-cost and market-impact models. AI can also help clients select and parameterize execution strategies based on the characteristics of an order or portfolio, while post-trade analysis can identify execution patterns and feed those insights back into future strategy selection. The opportunity is therefore not necessarily to replace established execution algorithms, but to make them more adaptive, predictive and easier for clients to use. Across FXGO more broadly. we’re continuing to invest in NLP across the platform with the goal of making the data that already exists on the Terminal actionable in ways that support faster, more informed execution decisions.
Is there anything coming up in the development pipeline you would be able to share?
The direction of travel across everything we’re building is toward giving clients deeper programmatic access across more instruments and more stages of the trade lifecycle, reducing manual touchpoints at every step, from pre-trade price discovery through to post-trade reporting. The pace of change is genuinely extraordinary right now, and the firms that will benefit most are those investing in the data and workflow infrastructure today rather than waiting for the technology to mature further.
