- Swift’s Project CALM uses AI and blockchain to improve corporate actions
- The project aims to reduce data fragmentation and manual errors
- Swift is pushing innovation in capital markets through tech integration
Swift Embraces AI and Blockchain for Market Efficiency
In a bold step toward modernizing financial infrastructure, Swift is advancing its corporate action processing through “Project CALM”, an initiative that leverages AI and blockchain technology. According to Duygu Kaya, Swift’s Capital Markets Strategy Director, the project aims to resolve some of the industry’s most persistent challenges—particularly data fragmentation and manual workflows.
Corporate actions—like dividends, mergers, and stock splits—are often delayed or miscommunicated due to inconsistencies across platforms. Swift’s Project CALM is designed to create a more streamlined, accurate, and efficient framework for handling such processes across global markets.
Solving Long-Standing Frictions with Tech
Project CALM (Corporate Actions Lifecycle Management) is Swift’s response to the legacy systems that have long plagued capital markets with inefficiency. Here’s how it addresses key pain points:
- AI for Automation: Machine learning is used to interpret and reconcile data, minimizing human error and speeding up decision-making.
- Blockchain for Transparency: Distributed ledger technology ensures a shared, tamper-proof source of truth for all participants, reducing communication gaps.
- Interoperability: The project is also focused on creating bridges between different market systems to tackle data fragmentation at its core.
Swift’s commitment to tech-driven transformation reflects a broader trend in financial services, where automation and transparency are becoming non-negotiable standards.
A Glimpse into the Future of Capital Markets
With Project CALM, Swift isn’t just testing new tools—it’s redefining the way corporate actions are handled across borders. As these initiatives mature, the financial industry could see faster settlements, fewer errors, and improved investor confidence.
Swift’s work underscores how AI and blockchain are moving from experimental to essential, especially in complex areas like capital markets infrastructure.
