Post-trade infrastructure is entering a period of structural change unlike anything the industry has seen since the regulatory reform that followed the 2008 financial crisis. Settlement cycles are compressing, trading hours are extending toward continuous operation, cross-asset strategies are demanding unified lifecycle management, and the tokenisation of real-world assets is opening new possibilities for collateral mobility and programmable workflows. Each of these shifts individually would place significant demands on the systems that underpin clearing, settlement, reconciliation and risk management. Taken together, they represent a fundamental challenge to post-trade architectures designed for a slower, batch-oriented world.
The response is taking multiple forms: incremental process re-engineering on existing platforms, AI-driven automation to eliminate manual touchpoints, central processing models that bring clearing-grade discipline to bilateral markets, and a new generation of standards-based orchestration layers designed to bridge legacy infrastructure and the programmable, always-on environment the market increasingly demands.So how are firms that operate across different parts of the post-trade value chain approaching this moment of transition, and where do the challenges and opportunities lie?
The growing strain on post-trade infrastructure
Post-trade infrastructure was not built for the world it now serves. The systems that underpin clearing, settlement, reconciliation and lifecycle management across global capital markets were largely designed for batch-oriented processing, overnight reconciliation cycles and a trading day with a defined beginning and end. That world is receding fast.
Rising trading volumes, cross-asset convergence, growing data complexity and the expansion of electronic execution are placing operational pressure on post-trade architectures that were never designed to handle this pace or breadth. At the same time, more than a decade of regulatory layering – from MiFID I through MiFID II, EMIR, Dodd-Frank and successive waves of reporting requirements – has left many firms with mid and back office infrastructure that has been repeatedly extended but rarely re-engineered.“Firms often hold the right securities but in the wrong place,” says Quentin Limouzi, Global Head of Post-Trade at Broadridge. “Inventory is spread across multiple depots, regions and affiliated entities, and operational teams have lacked real-time visibility to coordinate the movements.”
The problem runs deeper than data fragmentation. Much of the legacy post-trade landscape was built asset class by asset class, with front-office priorities driving the architecture. “Most legacy platforms were built as single-asset, front-office-first tools and only later added post-trade,” says Hristo Dinchev, CEO and Co-founder of AQX Technologies. “When clients asked for multi-asset, the common response was to bolt on new instruments and connect separate middle and back office modules via interfaces. The result is often a patchwork: multiple data models, duplicated controls, reconciliations between internal systems, and higher operational risk.”
The consequence is that post-trade is no longer just a back-office function. It has become a critical, load-bearing component of trading infrastructure. And one that is now being tested by a series of structural shifts arriving in rapid succession.
Settlement compression: T+1 and the process redesign imperative
The most immediate of those shifts is the compression of settlement cycles. The United States moved to T+1 in May 2024, and the United Kingdom and European Union are targeting October 2027. But while T+1 is often framed as a settlement challenge, its real impact is on the entire post-trade operating model.
“T+1 is often presented as a settlement topic, but in practice it’s a post-trade operating model issue,” says Dinchev. “Compressing two days of work into one means there is much less time for allocations, confirmations, breaks, FX, securities lending and funding to be resolved – especially in Europe with multiple time zones, currencies and CSDs.” For firms that have not modernised their workflows, the consequences are stark, observes Dinchev: “Miss the T+1 window or pay for more people and more overtime.”
Europe’s particular challenge is structural. Unlike the US, with its single CSD and relatively homogeneous market practices, Europe is a network of interconnected markets with different conventions, currencies and settlement infrastructures. “Europe’s move to T+1 is absolutely achievable, but it is not simply about faster settlement – it requires a fundamental operational shift,” says Val Wotton, Managing Director and Global Head of Equities Solutions at DTCC. “The greatest friction stems from the fact that Europe is not a single market, but a network of interconnected ones. Multiple CSDs, cross-border settlement flows, and different market practices across the region amplify the risks.”
The response from market participants varies. Some are pursuing large-scale transformation programmes; others are taking a more incremental approach. “Our recommendation is to move away from large, expensive transformation programmes and instead implement modular, value-accretive components that can be introduced incrementally,” says Limouzi. Broadridge’s experience of the US T+1 migration – where its platform supported clients through the transition – informs that advice, though Limouzi acknowledges that Europe’s fragmented clearing landscape introduces complexity that the US did not face.
Richard Baker, CEO of Tokenovate, argues that while T+1 is driving necessary process re-engineering, it is not the most significant catalyst for post-trade modernisation. “T+1 and Digital Regulatory Reporting are pushing the pressure, saying: we need to compress the lifecycle. But most companies are doing it on existing technology,” he tells TradingTech Insight. “Actually, it is the pressure on collateral mobility that is going to be the real catalyst for change.”
Wotton frames the destination clearly: “T+1 in Europe is less about raw speed and more about automating and harmonising post-trade workflows: earlier confirmation, standardised data, fewer exceptions, and more aligned operating windows across a complex market structure.”
From batch to continuous: the 24/7 challenge
Beyond settlement compression, a more fundamental shift is emerging. Major venues are moving toward extended trading hours – Nasdaq toward a 23-hour, five-day model for US equities – and digital asset markets already operate continuously. The question is no longer whether markets will trade around the clock, but whether the post-trade infrastructure behind them can keep up.
“The market can trade longer sooner than the industry can run longer, and that gap is where operational risk and manual work resurface,” says Dinchev. “Breaks in confirmations, reconciliations, margin and reporting don’t politely wait for the morning.”
The shift toward continuous operation challenges every assumption embedded in batch-based post-trade architectures: end-of-day processing, scheduled margin calls, periodic portfolio optimisation and reconciliation runs that depend on defined cut-off times. For clearing infrastructure, the implications are significant.
“Scheduled margin calls and end-of-day processing can still play a role, but they are unlikely to be sufficient on their own,” says Wotton. “The direction of travel is toward more dynamic, event-driven risk management, including intraday margining when volatility or concentration thresholds are breached, earlier identification of risk build-ups, and greater flexibility to extend processing windows without adding operational risk.” Importantly, he argues, this does not mean everything must become real-time: “A hybrid approach that includes structured cycles for predictability, supplemented by intraday capabilities triggered by risk, is the most pragmatic path forward.”
Some firms are already improvising solutions. Baker observes that proprietary trading firms are using stablecoins and digital rails to bridge the gap between traditional weekday infrastructure and weekend trading demand. “My Monday to Friday is my TradFi stack, but on Saturday and Sunday I can use some of these digital rails in the short term,” he says, characterising the approach he hears from CTOs. But there is a hard operational constraint: “We cannot have Saturday and Sunday look like Monday morning. It can’t be a backlog of trade exceptions, reconciliations and things to solve.”
Limouzi sees tokenisation as central to the answer, but frames its value differently from the conventional narrative around speed. “Tokenisation enables flexible settlement, not just faster settlement,” he says. “Traditional markets are constrained by fixed settlement windows and rigid operating hours. Tokenised infrastructure allows counterparties to agree programmatically, through smart contracts, on when settlement should occur – whether that’s in a day, intraday, or event-driven. Speed is a by-product; flexibility is the real benefit.”
Automation, AI and the end of manual post-trade
The operational pressures of settlement compression and extended trading hours are forcing a reckoning with how much of the post-trade lifecycle still depends on manual intervention. The gap between claimed automation and operational reality remains wide.
“Everyone in post-trade says they’re automated, yet many operations teams still spend a big part of the day copying data into spreadsheets, chasing emails and bridging gaps between disconnected systems,” says Dinchev. “The real issue isn’t the absence of tools – it’s that the workflow was never designed to run end-to-end without human touchpoints.”
Artificial intelligence is beginning to close that gap, particularly in the exception-heavy workflows that consume disproportionate operational resource. Broadridge has deployed OpsGPT, an AI-powered operations tool that is already delivering measurable results. “The most immediate impact of AI is around exception handling, workflow augmentation and operational research – areas that have traditionally required large amounts of manual effort,” says Limouzi. “OpsGPT is already cutting process time in areas like fail research, with firms seeing resolution cycles shrink from days to hours.”
Broadridge is also using the tool for predictive analytics, identifying potential settlement fails before they occur. “We do predictive analytics – predictive fails, for example – which in a T+1 world is very valuable because you’re not just real-time, you’re ahead of events,” Limouzi explains.
On the sell side, the automation challenge extends to portfolio optimisation workflows that remain surprisingly periodic. Andy Williams, CEO of Post-Trade Solutions at LSEG, describes the current state: “Today, when we optimise, we generally do it at a point in time. We might optimise margin once a week, or optimise capital every couple of weeks. You can definitely move those time horizons to daily once you have the right infrastructure in place.” The end-to-end automation of that cycle – collecting data, running optimisation, booking the resulting trades – is the core of LSEG Post Trade Solutions’ roadmap.
Real-time risk, capital efficiency and the central processing model
The drive toward automation intersects with a broader transformation in how post-trade infrastructure is used. What was once designed primarily to process transactions is increasingly being deployed to optimise capital, margin and balance sheet usage.
Nowhere is this more visible than in OTC derivatives, where the bilateral nature of uncleared markets creates structural inefficiency. Williams describes the problem: in the uncleared world, two parties face each other on a contract, each calculating valuations and cash flows independently using different systems, then reconciling and exchanging margin on a daily basis across thousands of counterparties.
LSEG Post Trade Solutions’ answer is a central processing model. “Within Post Trade Solutions, we often talk about delivering the benefits of clearing to the uncleared world,” says Williams. “What we really mean is a shift to central processing. Instead of each party calculating these things for the purpose of exchange, we calculate on their behalf what the valuation is, what the cash flow is, and we facilitate settlement – just as happens in clearing.”
The capital efficiency gains are material. Through Quantile, LSEG’s optimisation service, firms can rebalance counterparty risk without altering their market risk positions. “Margin runs can easily achieve a 50% reduction,” says Williams. “The range can be quite large – it could be 30%, it could be 70% – but around 50% is a reasonable average, depending on what the portfolio looks like.” These optimisation runs, initially a sell-side tool, are now increasingly attracting buy-side participation.
Underpinning the model is a move toward central, authoritative data. TradeAgent, LSEG’s recently announced affirmation service, is designed to be that foundation. “Once the trade has come into our database, it is authoritative,” says Williams. “Once you’ve got that central authoritative database of trades, you can drive all of the post-trade processes from it.”
The need for better intraday visibility is not limited to OTC markets. “If you ask mid-day, ‘What’s our overall position right now?’, the honest answer in many firms is: ‘Let’s wait for the next end-of-day run,'” says Dinchev. “That creates a timing gap – by the time overnight files are processed, markets may have moved and exposures may already be out of date.”
Baker frames the urgency through the lens of collateral. “The combination of market volatility, ongoing Basel-style rules putting pressure on capital adequacy and balance sheets, and the scarcity of high-quality liquid assets – those are trilemmas pushing firms toward needing to solve the collateral mobility problem,” he says. The tokenisation of real-world assets – bonds, money market funds, deposits – to make them eligible as collateral for initial margin, variation margin and settlement is, in Baker’s view, the bridge between process re-engineering and the longer-term atomic settlement opportunity.
Interoperability, standards and the strategic future of post-trade
If the operational pressures are clear, the architectural responses remain contested. There are different views on how post-trade infrastructure should evolve, and that divergence itself is a signal of how fundamental the current period of change is.
Baker argues that the industry needs to solve interoperability not at the blockchain protocol level but at the standards layer above it. Tokenovate has built its orchestration engine on the Common Domain Model (CDM), the open-source standard originally developed by ISDA and now maintained by FINOS. “The CDM is a deterministic state language model. Its only role is to describe financial products,” he explains. “Capital markets cannot run without certainty. You cannot have a probabilistic outcome; you need a deterministic outcome.”
Tokenovate writes smart contracts at the native CDM level, making them agnostic to the underlying infrastructure. “It doesn’t matter whether I’m running down an OSTTRA pipe or an LSEG pipe, or whether I’m going down a Circle or Ripple pipe, or any blockchain,” says Baker. His critique of the current landscape is pointed: “We know that public blockchain technology is the future, but we’ve missed standards. The industry has generated an interoperability problem at the blockchain level and an interoperability problem at the tokenisation level.”
Williams shares the enthusiasm for CDM – “TradeAgent has implemented CDM as the data model,” he confirms – but diverges sharply on the question of distributed ledger technology. “For us, we believe very strongly in central ledger as opposed to distributed ledger,” he says. “Distributed ledger in the OTC world is not necessarily solving a problem. You’re not lacking central trust – in fact, you have central trust through FMI operators like LSEG.”
On tokenisation, Williams draws a clear line: collateral is a near-term opportunity, but OTC instruments themselves are not. “I’m not expecting OTCs to be tokenised any time soon. I’m not sure what benefit that necessarily brings. Tokenisation of collateral, though – we do expect to see that.”
Wotton places tokenisation within the broader context of market infrastructure evolution: “Tokenisation enables real-time, 24/7 movement of high-quality liquid assets and unlocks exceptional value when combined with the risk controls, legal certainty, and governance frameworks that underpin today’s markets.”
What unites all five contributors is the conviction that the post-trade layer is no longer peripheral to competitive positioning. “The market demands efficiency now. Becoming more efficient in post-trade is not a choice,” says Williams. “When you do it well, you can save a significant amount of capital and increase your returns. Those are the metrics that everybody cares about.”
Wotton sees the shift in strategic terms: “There is growing recognition across the industry that high-quality post-trade data and automation are critical enablers of accelerated settlement, as they support greater risk mitigation, improved efficiency and fewer exceptions. Automated post-trade processes are increasingly being viewed as a foundation for future market resilience and growth.”
The modernisation of post-trade technology is no longer a back-office upgrade project. It is becoming a strategic industry priority. The firms that recognise that earliest are likely to be the ones best positioned for whatever comes next.
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