DEEP LOOK | As securities services providers increasingly differentiate themselves on how their post-trade infrastructure operates, genuinely integrated workflows are becoming a key component of the competitive proposition.
J.P. Morgan’s 2026 Markets e-Trading Survey notes that delays between execution and post-trade processing can increase funding costs, tie up collateral and create operational risk for traders.
According to the report authors, this is pushing institutions towards integrating these typically separate functions into a single workflow, so execution, analytics, collateral management and settlement operate together rather than working in silos. The survey found that the development of financial market technology is now the leading preoccupation of institutional traders.
Nate Wuerffel, head of market structure and head of product for the global collateral platform at BNY refers to a combination of forces changing not just how transactions are executed but also making the economics of trading more complex and challenging to assess on a fully loaded risk, return and cost basis. “For example, in a cleared repo transaction, firms are no longer solely focused on the traded rate,” he says. “They also need to consider the cost of capital, liquidity, intermediation and intraday funding, as well as the risks associated with more complex clearing models.”
To navigate that complexity, firms are increasingly looking to AI for greater visibility and insight before the trade, while also exploring digital platforms and assets that could improve efficiency across the process.
When post-trade data becomes a firm’s golden source
Mack Gill, head of securities processing for FIS Capital Markets suggests that with APIs and real-time processing, front-to-back workflow can and should be seen as a single, integrated process – even with a combination of different vendor and in-house components. “With the global move towards ‘always-on’ markets, real-time, event driven, intraday processing is becoming increasingly vital in post-trade,” he says. “The back office is moving from a 24-hour batch cycle to a real-time processing engine and leveraging post-trade data for trading analytics is becoming more prevalent as firms look to leverage their post-trade data as their firm’s ‘golden source’, not just for standard reporting.”
Gerard Walsh, global head, market solutions, banking & markets at Northern Trust says his institution has always viewed the full lifecycle of the trade, trade-related FX, risk management processes, matching, clearing and settlement as a single workflow. “It is one of the reasons our front office operations teams and their technology sit in the same room as our trading teams,” he says. “The single workflow is real and that proximity is a major benefit to managers/investors who choose to trade with us.”
Trading processes have always relied on hand-offs and interactions between systems, processes, people and multiple internal and external market participants to complete the trade. Walsh adds that the focus recently has been on technological refinements to lower the costs and risks of interaction at each handover point within the lifecycle.
The interoperability hinge
While the aspiration is seamless real-time connectivity, interoperability remains a work in progress. As a middle office provider, State Street operates within a highly interconnected ecosystem, receiving electronic trade records and interacting with numerous brokers, custodians and market infrastructures explains Ben Buchan, head of EMEA trade management.
“While some firms are moving towards fully integrated workflows, we believe the greater opportunity lies in connected ecosystems that enable the free flow of information across functions, reducing manual intervention and operational friction,” he says.
The issue is who can use the technology best to remove friction between different parts of the transaction lifecycle. For securities services, that means reducing the number of interfaces clients have to manage, automating processes and connecting clearing, settlement, custody and collateral more effectively.
Simpler, smarter, speedier
The benefit will ultimately be lower operational complexity, better use of capital and the ability to respond faster as markets and regulations change, which will increasingly influence how institutions choose their post-trade partners. That is the view of Urs Walbrecht, head of sales & relationship management at SIX Securities Services, who cautions that capital markets still contain a considerable amount of legacy technology and separate systems that were built at different times to solve different problems.
“It is becoming common for execution, analytics, collateral management and settlement to operate in a single workflow but I would distinguish between genuine integration and simply having several services available from the same provider,” he says. “The industry is moving towards fewer touchpoints and more connected workflows but there is still considerable fragmentation between execution and what happens afterwards.”
Interoperability: a marathon, not a sprint
Being able to identify eligible collateral, mobilise it and meet a margin call quickly can reduce the amount of capital a firm needs to keep sitting idle, which is where an integrated workflow starts producing a measurable financial benefit rather than simply an operational one. Alison Higgins, global head of prime services at Standard Chartered agrees that post-trade capabilities are becoming an important source of differentiation. She notes that as traditional finance and digital asset markets continue to converge, clients increasingly expect seamless servicing across asset classes, real-time visibility and more efficient collateral and liquidity management and describes post-trade innovation as a natural evolution of the market rather than a standalone technology race.
“The industry has made significant progress but real-time interoperability is not yet universal,” she adds. “While many leading institutions have invested heavily in integrating front-to-back workflows, the reality is that most market participants still operate within a complex ecosystem of internal platforms, third party vendors and market infrastructures.”
In normal market conditions, these systems generally function effectively. However, periods of market stress often expose connectivity gaps, data inconsistencies and manual intervention points.
“The direction of travel is clearly towards greater real-time integration but the degree of seamlessness varies considerably across firms depending on their operating model, technology stack and level of investment,” says Higgins, who shares the view that execution, analytics, collateral management and settlement operating in a single workflow is far from the industry norm.
“The more important trend is not necessarily consolidation onto one platform, but the ability to create a consistent data layer and workflow across interconnected systems,” she adds.
AI and digital tech: filling the fragmentation gap
In highly liquid markets, firms are generally more likely to have tighter connectivity across workflows, from execution through settlement. In more complex markets – especially those that are balance sheet, capital or liquidity intensive, span across multiple asset classes or involve more complex risk factors – it can be harder to model the process end-to-end. Those markets often rely on more bespoke systems and tend to have less workflow automation.
As a result, Wuerffel observes that many market participants are still managing trading, settlement and risk across a number of legacy platforms that do not communicate with each other as seamlessly as they should.
“AI has the potential to be especially powerful in this context because it can create an intelligence layer across those fragmented systems, supporting both decision making and workflow management – an advantage that could be especially valuable in more volatile markets,” he says.
At the same time, digital technologies such as atomic settlement and smart contracts could help make processes faster, more synchronised and more efficient.
“The combination of AI and digital technology could prove especially powerful, bringing together trade intelligence, speed and end-to-end workflow management in ways the market has not yet fully realised,” says Wuerffel. “But scale matters here too: these capabilities are most valuable when built on top of large, liquid networks.”
More than the price of execution
Kate Finlayson, global head of FICC market structure & liquidity strategy at JP Morgan observes that market participants and investors are looking at how they access and interact across platforms and engage with liquidity, how they consume market or trade data, how they assess not only liquidity but also their choices in how and where they execute.
That also includes on a post-trade basis evaluating the execution, the trading techniques that they employed. Post-trade analysis is well established when firms assess execution quality, but Walbrecht reckons there is an argument for taking that mindset much further. “A successful trade should not only be judged by the price at which it was executed,” he says. “Firms should also be asking what it subsequently cost to clear, how much margin and collateral it consumed, where it settled and whether a different post trade route could have produced a better overall economic outcome.”
Walsh refers to better data as being instrumental in improving the usefulness and viability of post-trade evaluation. The most tangible example is best execution data, which continues to improve in usefulness as data richness increases and understanding of the variabilities of what makes ‘best execution’ improves across the industry.
Trade execution is no longer the sole focus for market participants. Settlement efficiency, confirmation timeliness, straight-through processing rates, failed trades, related costs and counterparty performance all remain key priorities for both service providers and clients.
“As markets become faster and more complex, post-trade data is increasingly being used to generate insights into operational effectiveness, risk management and investment performance,” says Buchan. “Overall, the industry is evolving towards highly automated, data-driven and exception-based operating models, where operational excellence is becoming a genuine source of competitive advantage.”
