Evolution of Post-Trade Infrastructure: How Artificial Intelligence is Impacting CCP and CSD Modernization

Artificial intelligence (AI) promises to reshape capital markets and the trade lifecycle. And as AI use cases rapidly move from experimentation to deployment, the future shape of post-trade infrastructure providers is coming into focus.

This shift presents both opportunities and challenges to central counterparty clearing houses (CCPs) and central securities depositories (CSDs). While AI-automated workflows and intelligence offer efficiency and new revenue streams, they require strategic thinking across the scope of post-trade infrastructure.

At the heart of these considerations is technology and market platforms. But data management, operations and member impact must also be addressed for AI initiatives to succeed. Here is a closer look at the potential use cases in post-trade and how CCPs and CSDs can navigate the modernization pathway.

In clearing, AI is being used to enhance margining risk models by analyzing vast datasets of historical transactions, market conditions and counterparty behavior. This allows CCPs to move toward predictive analytics and collateral adjustments and real-time stress testing with greater precision. 

In custody, AI can enable reduced settlement exceptions and improved reconciliation workflows. Machine learning models can detect anomalies in trade data, flag potential mismatches and suggest resolution based on historical patterns. These capabilities not only accelerate settlement cycles but also reduce operational overhead—freeing teams to focus on exception management, client service and other strategic initiatives.

These developments align with findings from a new survey by Nasdaq on Asia-Pacific markets. In it, we asked nearly 400 market participants on their operations in the region and found that institutional firms are embracing AI in key post-trade areas, showing operators and participants are on the same accelerated adoption path:

• 14% plan to use AI in onboarding by 2028
• 11% plan to use AI in trade clearing and settlement by 2028
• 10% plan to use AI in corporate actions and reconciliations by 2028
• 7% plan to use AI in collateral management by 2028
   

AI has several applications in the operations of infrastructure providers and in the products and services they offer. Within the business, automation reduces manual intervention in processes. This leads to faster cycles, lower costs and increased accuracy, freeing staff to focus on higher-value tasks. By embedding AI-driven tools directly into their operational workflows, these institutions can generate near-term savings while laying the ground for longer-term realization of value through agentic AI and generative AI.

Beyond efficiency, AI enables market infrastructures to offer real-time, tailored insights and dynamic services to participants and members. These advanced capabilities, like real-time analytics, chatbots and data copilots, to help improve transparency, enable self-service and support better decision-making for clients.

One use case to consider is AI assistants. In a post-trade context, assistants can help enhance user engagement across a range of often repetitive and highly manual tasks in onboarding, daily operations, data analysis and forecasting. By leveraging natural language processing models and contextual understanding, these assistants allow users to obtain information and support without the need for specialized technical skills or manual procedures.

An AI assistant can empower staff to:

• Set up clearing products in minutes without needing to reference a manual.
• Reconfigure member access and get logic-based automated guidance on local customizations.
• Answer a clearing member’s question with instant rulebook or fee schedule references.
   

To leverage AI, CCPs and CSDs must address fundamental technology architecture considerations. This extends beyond the scalability and modernization of mission-critical clearing and custody solutions. Importantly, data management is at the heart of successful AI deployment.

Also important is integration and interoperability. Ideally, infrastructure providers can access AI capabilities that are naturally embedded in existing workflows, rather than bolted-on point solutions, which could lead to fragmentation and degradation of data quality. Still, as a number of commercial large language models (LLMs) gain traction, CCPs and CSDs benefit most modernized infrastructure that feature open architecture able to integrate with preferred models. In the highly risk-sensitive and specialized operations of these institutions, tailored AI experiences can help meet unique operational needs and technology preferences as they evolve.
 

For CCPs and CSDs, the question is not whether to adopt AI but where and how to deploy. Adoption is a curve and market operators can create and sustain initial momentum for AI by using it to replace manual tasks and enhance value-add. Efficiency gains are just the starting point. The real opportunity lies in using AI to reimagine service delivery, unlock new revenue streams and position post-trade infrastructure as a competitive advantage.

Nasdaq Eqlipse Post-Trade platforms—Nasdaq Eqlipse Clearing and Nasdaq Eqlipse CSD—are evolving alongside these trends to embed AI assistants within our infrastructure solutions. With these tools, users can benefit from:

• Faster system tasks and simpler onboarding.
• Fewer configuration errors, requiring less tech support.
• Real-time data access and reduced spreadsheet dependency.
• Lower analyst workload and costs with self-service reporting.
• Scalable model supporting many clients at reduced to no cost.

The dual value-creation model—cost savings through automation and revenue generation through premium analytics—is particularly compelling. By offering AI-powered self-service portals, market operators can monetize access to product insights and transactional analytics, while simultaneously reducing the burden of manual report generation and client support. This scalable approach allows infrastructure providers to serve a broader participant base without proportional increases in operational overhead. Moreover, the ability to query live data, simulate risk scenarios and surface anomalies in real time is game-changing.

Collaboration will be key to the future of AI in the post-trade space. Finding the right technology partners will be critical to the AI strategy of CCPs and CSDs and their own member ecosystems. Working with Nasdaq Financial Technology can help institutions not only gain purpose-built solutions for mission-critical infrastructure but also an experienced capital markets partner. Operators, participants and technology providers collaborating together can help expand AI use cases, accelerate adoption and create best practices around factors like cloud enablement, governance and data management.

Discover How Nasdaq Financial Technology Empowers Over 3,800 Leading Finance Organizations

We are committed to helping market operators and participants overcome infrastructure, operational and regulatory challenges. Our solutions empower you to focus on your core competencies, driving market growth and progress.

Learn More