Shifts in Post-Trade: Case Studies and Infrastructure Principles for Success

Post-trade operations are at the center of a market environment with increased complexity, accelerated settlement cycles, expanded asset classes, and heightened regulatory expectations. For firms navigating the structural change, this article examines the forces reshaping post-trade processes. We use two case studies as examples—accelerated settlement and digital asset adoption—and offer perspective on how firms can build adaptable foundations to stay ahead of changes.

More Volume, More Complexity, More Variation

Always intricate, post-trade workflows today are increasingly shaped by factors outside any one institution’s control. For example:

• Regulatory reporting regimes have expanded in scope and specificity across jurisdictions.

• Trade volumes continue their long-term climb.

• New asset classes and multi-market workflows bring new data sets, reconciliation requirements, and partner dependencies.

Many firms are balancing these pressures while managing expectations for margins, efficiency, and transparency.

In that context, scaling operations requires coordinated investment, clear ownership, and a strategic lens on where standardization is possible and where variation is acceptable.

In short, the demands on post-trade infrastructure are multiplying unevenly across jurisdictions, markets, and counterparties. The variability is compelling leaders to treat modernization as an enterprise priority with operating models that evolve cohesively rather than market by market. The following two examples illustrate this dynamic.

Example No. 1: The Global Journey to T+1

The move to T+1 in the United States and Canada provided valuable lessons about data quality, workflow automation, and the operational strain that compressed timelines created for firms. But the next phase of accelerated settlement—Europe’s planned transition in 2027—illustrates the greater complexity of a highly fragmented market structure that includes a range of operational and structural challenges, including:

• A dispersed market landscape, with numerous CSDs and settlement frameworks that must align under a single T+1 timetable.

• Cross-border trading patterns that add extra touchpoints, dependencies, and regulatory coordination.

• FX settlement misalignment as cash and securities move on different cycles across jurisdictions.

• Asset class variation with differing impacts on equities, ETFs, securities lending, and fixed income across European markets.

• Compressed affirmation and funding windows complicated by multiple time zones and national holidays.

Those circumstances highlight how regulatory and industry change rarely unfold in a uniform way across jurisdictions, even with the shared end state of T+1. For firms operating globally, the differences introduce real complexity. Building processes that are consistent at the core yet flexible enough to absorb jurisdiction-specific requirements is essential for achieving scale and maintaining resilience across an increasingly interconnected marketplace.

Example No. 2: The Rise of Digital Assets

Digital assets and distributed ledger technology are also influencing post-trade operations. Unlike accelerated settlement, which compresses existing processes, digital assets introduce new market structures altogether. Per a Citi survey, more than 80% of institutions expect digital assets to materially change how markets operate in the years ahead. Changes are already visible across tokenization pilots, emerging custody frameworks, and efforts to integrate DLT into traditional post-trade workflows.

The rise of digital assets creates distinct post-trade challenges, including:

• Hybrid rails, as traditional and DLT-based settlement infrastructures operate in parallel and require coordinated workflows.

• Longer servicing horizons, since certain tokenized products may require near-continuous asset servicing across venues.

• New data and reconciliation rules, driven by different asset representations and faster settlement mechanics on DLT networks.

• Wider counterparty variation as issuers, custodians, and brokers adopt digital asset frameworks at different speeds and with different standards.

• Inconsistent regulatory models given digital asset requirements differ materially across jurisdictions.

Even as firms prepare for these specific operational demands, the broader implication is that digital assets are not a one-off challenge. Their use cases, market structure interactions, and settlement behaviors will likely continue to evolve faster than traditional infrastructures. The real requirement for firms is to build a post-trade foundation capable of absorbing whatever comes next.

Adaptable Post-Trade Infrastructure

Every firm’s operating model is different, but several principles underpin the leading post-trade environments:

Building for the Unknown

The example we discussed—shifts toward T+1 and digital-asset adoption—illustrate how quickly post-trade processes can be reshaped and how unevenly change can unfold. Firms cannot assume that regulatory, technological, and operational transitions will advance in a coordinated way. Instead, they prepare to absorb variation, ambiguity, and moments of rapid acceleration.

Looking ahead, the larger challenge is building a post-trade foundation capable of adapting to many scenarios. There will be a continuation of new asset types, market acceleration, and jurisdiction divergence. Firms that invest in flexible data models, interoperable architectures, sustainable automation, and thoughtful applications of AI will be well positioned to navigate future changes.

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