How has the role of FX market data changed over the past five years, and what are the biggest drivers of that change?
The FX market has been electronic for a long time, and real-time data was never optional. What has genuinely shifted over the past five years is how many jobs one dataset now must do at once: from valuation and reporting through to live execution, risk management, and regulatory compliance, often simultaneously and within the same workflow. Indicative pricing remains as important as ever for tasks like curve construction, model calibration, and pre-trade analysis, but it is no longer enough on its own. Our clients now also require deeper layers of market intelligence alongside it.
Electronification has intensified that demand, systematic trading has raised the bar on consistency and historical depth, and regulatory requirements have made data provenance a front office concern rather than simply a post-trade consideration.
At Fenics Market Data we have built our offering to serve this full range of needs, from comprehensive indicative pricing sourced from genuine interdealer activity through to liquidity insights and raw order and trade data for clients who need the most granular view of what is happening in the dealer markets.
To what extent has market data become a competitive differentiator rather than data as a service?
It has become a differentiator, without a doubt. The gap between “Data-as-a-Service” and “Intelligence-as-a-Service” is really a gap in what clients now ask of it. Data-as-a-Service gets you a price. Intelligence-as-a-Service gets you a price plus the context to know whether to act on it or wait.
Now clients stack real order and trade data, liquidity analytics, and execution benchmarking on top. That higher bar is what has separated providers over the past few years, not the accuracy of the raw feed itself, which has mostly converged across the industry.
Our pricing draws on one of the largest interdealer networks in FX, so the raw feed starts strong, and our Solutions service layers real order and trade data on top for clients who need to see execution conditions, not just a quote. Bring these capabilities together, and data stops being simply an input that firms buy and becomes something they can build a strategy around.
How is the explosion of electronic trading venues reshaping the FX data landscape?
More electronic venues have created more data, but also a more complex aggregation challenge. Liquidity is now spread across ECNs, single dealer platforms, bilateral streams, and internalised flows, and making sense of all of that requires careful normalisation and weighting rather than simple consolidation.
As leading dealers internalise a growing proportion of client flow, a significant share of real market activity never appears on public venues at all making the sourcing of data as important as its aggregation.
Indicative pricing remains the backbone of how most firms navigate this landscape for valuation, pre-trade, and reference purposes, while real order and trade data adds the granular layer needed to understand actual execution conditions.
What structural changes in FX liquidity are most visible through the data you provide?
The most visible structural story is the growing divergence between the major pairs and the rest of the market. In G10, liquidity is deep and electronification is mature, so the data challenge is about precision, latency, and microstructure detail. In emerging market currencies, exotic crosses, and NDFs, the challenge is more fundamental: consistent, reliable coverage across the full curve has historically been harder to achieve, and the cost of gaps or distortions in that data is real.
The second clear trend is the continued growth of internalisation, with dealers absorbing more client flow on their own books. That makes independently sourced interdealer data, both indicative and transactional, increasingly valuable for understanding where prices are genuinely forming. Our indicative pricing provides broad and consistent coverage across both the liquid core and the less liquid segments, while our L2 service gives clients who need it a direct window into real order and trade activity from BGC Group’s interdealer network.
How are shifts in market microstructure influencing the types of data clients now demand?
The clearest shift is towards wanting multiple layers of market intelligence rather than just a single price. Indicative pricing remains the foundation. It is what firms use for valuation, model inputs, pre-trade reference, and regulatory benchmarking. But clients increasingly want to complement it with a richer understanding of market conditions. How deep is liquidity at a given moment? How are spreads behaving? What does the order book look like? As execution becomes more automated, these questions are more relevant than ever. Regulatory expectations around best execution have also increased the importance of being able to demonstrate how trading decisions were made. Achieving a good fill is no longer enough on its own; firms increasingly need the data and analytics to show the market conditions that prevailed at the time, the liquidity that was available and the basis on which an execution decision was taken.
How is access to more granular data changing decision making in FX trading?
Granular data has significantly enhanced capabilities across every stage of the trading workflow:
In the pre-trade phase, firms can now develop a more comprehensive view of market conditions, gaining insight not only into current pricing but also into market positioning and the true depth of available liquidity.
During execution, high-quality real-time data feeds directly into algorithms and pricing engines, with the accuracy and timeliness of these inputs playing a critical role in determining execution performance.
Post-trade, the availability of detailed data enables robust benchmarking against actual market conditions, making execution quality both transparent and measurable in ways that were previously unattainable.
In what ways are FX trading strategies becoming more data driven and systematic?
Systematic strategies in FX have been around for many years, but what has changed is how demanding they have become about data quality across the full curve and over time. Back testing requires historical data that is consistent and free from distortions. Gaps or anomalies in less liquid tenors introduce biases that carry through into live strategy behaviour in ways that can be very hard to diagnose. Reliable indicative pricing is the natural input for most of this work: it provides the broad, consistent coverage across instruments, tenors, and currency pairs that systematic model development depends on. For strategies that also require execution level insight, the understanding of real order flow dynamics and validation of trading signals against actual transaction data is a key component, which is evident in FMD’s Trade & Order solutions.
How have regulatory expectations reshaped demand for FX market data?
Regulation has elevated data provenance and methodology from a matter of quality to a core compliance requirement. Under MiFID II, firms are expected to demonstrate that pricing and execution decisions are based on transparent and defensible inputs. More recently, the December 2024 update to the FX Global Code introduced clearer obligations around the use of client-generated data on trading platforms, as well as greater transparency in how execution in delegated execution is disclosed.
Within this framework, indicative pricing that is supported by corroborating observable prices and a robust methodology addresses a significant portion of these requirements. It provides a consistent and auditable reference layer that firms can readily explain, justify, and defend in both internal governance and regulatory contexts.
isn’t managed on its own anymore
How is AI and machine learning changing the way FX market data is consumed and analysed?
AI is only as good as the data behind it, and two shifts are changing how firms use it. Natural-language interfaces are replacing dashboards and query languages, so a trader can ask a plain question about counterparty behaviour and get an instant answer, no coding required. AI is also moving into flow classification while a trade is still live, flagging toxic flow in real time rather than diagnosing it the next day in TCA.
Underneath both, model quality still comes down to the data: a model trained on sparse or inconsistent inputs will produce confident, wrong answers. This shows up clearly in EM and NDF curves, where CNY turnover alone grew 56% over the three years to April 2025, and interpolation trained on genuine market observations is starting to outperform traditional methods. Better inputs, not just better algorithms, are what’s driving the improvement.
What new types of analytics and FX data products do you expect to emerge?
The direction is convergence, not one flashy new product. Indicative pricing, order and trade data, liquidity depth, and volatility surfaces have historically shipped as separate feeds that clients reconcile themselves. The demand now is for a provider to hand over that reconciliation already done. Liquidity heatmaps, once a specialist add-on, are becoming a standard layer sitting alongside pricing, giving traders a live view of depth and likely market impact before they size an order, not after.
Volatility surfaces for less liquid pairs and NDF tenors are the clearest gap left to close, and it’s opening fast as those markets electronify. The other real shift is FX data getting pulled into multi-asset risk frameworks, because cross-currency exposure isn’t managed on its own anymore, it sits inside a broader portfolio view.
Our own roadmap follows that logic: building the reconciliation between pricing, order flow, and liquidity analytics into the product itself, rather than leaving clients to stitch it together afterwards.
How is the relationship between FX data providers and consumers evolving?
Clients increasingly expect data providers to understand their specific workflows, whether focused on valuation, systematic trading, execution benchmarking, or regulatory compliance, and to deliver solutions that integrate seamlessly without requiring significant internal development.
Indicative pricing and real order and trade data address distinct use cases and are consumed in different ways, making it essential to align the appropriate data layer with each application. A strong data partner adds value by helping clients determine how best to deploy these datasets, rather than approaching all requirements as a single, uniform challenge.
Fenics Market Data is structured around this principle. Our indicative pricing and Level 2 offerings are designed as complementary but independent solutions, allowing clients to use them separately or in combination depending on their needs.
We also provide flexible delivery options, including real-time streaming feeds, snapshot data, and end-of-day datasets, ensuring clients can access and consume the data in a format that aligns with their operational and analytical workflows.
Leveraging BGC Group’s central position in the interdealer market, both datasets are grounded in genuine market activity. Our focus is on making this intelligence readily accessible and easy to integrate into existing client infrastructure.
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