In FX, liquidity is only as real as the market impact it creates—particularly in Scandies, where depth is less resilient. This reflects the reality of a highly fragmented market, where liquidity is dispersed across multiple venues and inconsistent depth. Algorithmic execution provides a structured way to aggregate liquidity, reduce signalling risk, and optimise execution through adaptive routing and order placement. These benefits become even more critical in illiquid currency pairs, as limited depth increases sensitivity to order placement, routing logic, and market impact. We see algorithmic execution volumes in Scandies steadily increasing, as market participants turn to automated strategies to better navigate less resilient liquidity.
Liquidity conditions differ materially across currency groups. Major pairs tend to exhibit deeper and more resilient liquidity, while Scandie liquidity is typically thinner and more fragile. This also amplifies time-of-day effects in regional pairs, where execution quality can deteriorate markedly outside local market hours, unlike in more liquid currency pairs where liquidity remains more consistent globally.
Internalisation
In these environments, internalisation becomes a key driver of execution quality. For Scandies in particular, performance depends heavily on access to a strong client franchise with natural, two-sided flow. A broad and diversified client base, spanning corporates, institutions and retail, enables risk offsetting without relying on external liquidity. This diversity is essential for achieving stable and scalable internalisation.
It is also important to recognise that the definition of internalisation has evolved across the market, prompting increased focus on standardisation and best practices. Our approach is deliberately conservative, classifying flows as internalised only when offset against genuine client flow, actively sourcing liquidity from carefully curated, skew-safe client pools.
Adapting execution strategies to different market conditions is essential. The same execution parameters can appear passive in one environment and aggressive in another, reinforcing the need for dynamic configuration aligned with prevailing market conditions. This also extends to how skew is presented to clients, where robust leakage controls are required to prevent pricing adjustments from becoming unintended market signals.
Liquidity is fragmented and often deceptive due to a liquidity mirage; where displayed depth fails to materialise upon execution; visible market depth can vanish the moment you try to execute a trade. This underscores the need to carefully evaluate where and how to trade, rather than relying strictly on displayed prices.
Ongoing assessment of liquidity providers is therefore critical, incorporating metrics such as fill ratios, execution consistency, and price decay. A venue offering a tighter top-of-book price may still underperform if it cannot deliver reliable size. In such cases, the cost of missed execution can outweigh the apparent pricing advantage, making consistency a more valuable attribute than spreads.
Liquidity reliability
Across FX trading, and particularly in algorithmic execution, the focus is increasingly shifting towards long-term liquidity reliability. It is not only about how liquidity is priced, but how it behaves, how it recycles, how consistently it fills, and how execution quality holds across different volumes and market regimes.
For market participants willing to absorb time risk, algorithmic execution provides direct access to internal franchise flows combined with full transparency on execution outcomes. Effective liquidity management, including continuous optimisation of how flows interact, has enabled us to further improve internalisation levels, both within algorithmic execution and more broadly. Taken together, regional banks have a structural advantage through superior access to unique liquidity, even as international competition seeks to challenge it.
