For all the progress electronic trading has made over the past two decades, the actual experience of being an institutional client on an algo platform still feels stuck in an earlier era – and the industry doesn’t talk about it enough. The technology is fast. The service model wrapped around it is not.
Naz Al-Khudairi
Start with analytics. Clients are trading in real time, and the decisions built on top of that flow – adjusting an algo mid-session, redirecting an order, sizing the next clip – need to happen in real time too.
Yet the recommendations and analytics meant to inform those decisions frequently don’t show up until the next day, if at all. Real-time insight into execution quality or algo performance should be table stakes; instead, it’s treated as a stretch goal. By the time a client sees the numbers, the moment they needed them for has already passed.
Then there’s customisation. Every institutional client eventually wants something tailored – a tweak to an algo’s aggression, a parameter adjusted for a specific liquidity profile, a workflow built around how their desk actually operates.
On paper, this is exactly the kind of value-add that should differentiate one platform from another. In practice, it takes weeks. Not because the underlying change is technically difficult, but because the process connecting a client’s request to an engineering team’s output is manual, sequential, and slow. Weeks of lead time on a request that should take days sends a clear signal to clients about how much flexibility they’re actually going to get.
The support model has its own bottleneck. Sales traders are the front line for client questions about algo behaviour, order handling, and execution logistics, but they’re rarely equipped with the quant-technical depth to answer those questions on the spot.
Every non-trivial question gets kicked upstream to a quant or engineering resource, and the client waits. That lag compounds: it’s not just slower service, it’s service that feels reactive rather than expert, at exactly the moment clients are trying to decide how much they trust a desk with more of their flow.
And finally, there’s the commercial distortion this all creates. When the electronic channel can’t handle anything beyond the basics, clients who want more sophisticated execution – anything requiring real judgment or customisation – get funnelled onto high touch desks by default. That means higher commissions for services that, in principle, should be deliverable electronically at a fraction of the cost.
It’s not that high touch desks shouldn’t exist; it’s that clients are being pushed there by platform limitations, not by genuine need, and paying for it.
Viewed collectively, these issues are not isolated friction points. They point to a single fundamental flaw: algorithmic trading platforms were engineered to match orders against benchmarks efficiently, but failed to support the surrounding institutional relationship in real time.
This naturally raises the question of why the gap persists. The technical barriers are minimal. Instantaneous execution metrics, rapid parameter adjustments, and accessible algorithmic insights require no fundamental technological leaps – the requisite technology has existed for years.
The reality is that major market participants lacked the incentive to modernise. Sophisticated orders that fall outside basic electronic capabilities are directed toward high-touch desks, preserving lucrative commission streams.
Fully resolving electronic limitations risks cannibalising that business. This economic trade-off has been repeatedly accepted across sell-side institutions, driving the current state of client-facing infrastructure far more than engineering constraints ever did.
Certain transactions undoubtedly demand high touch handling. Significant block sizes, illiquid securities, or trades necessitating principal risk taking and human market intuition justify their costs. The issue stems from secondary flow migrating to high touch desks simply because electronic alternative platforms remain incomplete.
This status quo represents an intentional strategy rather than a technical limitation, and institutional clients are recognising the distinction.