A.I.-based technologies, trusted data, and human expertise are joining forces to potentially reshape the corporate actions processing landscape, says Jatan Pathak at S&P Global Market Intelligence in an FTF News Q&A.
Jatan Pathak
(Corporate actions processing has many moving parts activated by market-related moves by public companies that can potentially impact securities, investors’ decisions, and stakeholders. The key steps of the corporate actions process include capture, validation, entitlement calculation, and asset or cash distribution, which has historically been a maze of automated and manual steps. However, the onset of artificial intelligence (A.I.) technologies, a strong focus on trusted data, and the many facets of human expertise could reshape corporate actions processing as we know it, says Jatan Pathak, global head of corporate actions data and managed services at S&P Global Market Intelligence, via an FTF News Q&A. S&P Global Market Intelligence won the FTF Award this year for Best Corporate Actions Service Provider for its Managed Corporate Actions (MCA) offering. Pathak recently took time out of his busy schedule to answer our questions.)
Q: Why do you think S&P Global Market Intelligence won the FTF Award for Best Corporate Actions Service Provider this year?
A: I believe the recognition reflects the combination of scale, data quality, domain expertise, and operational rigor behind our Managed Corporate Actions (MCA) offering. Corporate actions data is operationally critical, and errors or delays can have direct financial and downstream processing consequences for clients. That makes accuracy, timeliness, and control particularly important.
We cover millions of securities across more than 170 markets, spanning 65-plus corporate action event types and sourcing information from more than 200 sources globally. Last year alone, MCA published more than 40 million unique corporate actions across global markets.
What differentiates the service is that we are not simply aggregating corporate actions data. Our global teams source, interpret, validate and standardize complex information across markets, languages and source types, creating a consistent, actionable data set that clients can use within their operational workflows.
That combination of broad global coverage, high-quality normalized data, and deep corporate actions expertise is particularly important in a data set where accuracy and reliability are critical. Ultimately, I think the award reflects both the strength of the service and the trust our clients place in the data every day.
Q: How is S&P Global using its corporate actions expertise to enhance the application of large language models (LLMs), and what does that involve?
A: Corporate actions have their own highly specialized language, terminology, and event structures. MCA has more than 24 years of robust corporate actions data history across markets and event types, together with the issuer-linked source documents from which our validated ‘golden copy’ data was created.
We are using that depth of historical data, source documentation, and domain expertise to help large language models better understand how corporate actions information is expressed, interpreted, and standardized. The objective is to improve the ability to extract, classify and interpret complex, often unstructured information and turn it into accurate, actionable corporate actions data.
Q: How does this combination of proprietary data, domain expertise, and A.I. create new opportunities for S&P Global’s corporate actions services?
A: The combination of trusted historical data, issuer linked source documents and deep corporate actions expertise gives us a strong foundation for applying A.I. in practical, high value ways.
We are already seeing tangible impacts through capabilities such as our Operational Intelligence Hub, A.I.-generated data summaries, and direct data conversion, which help users surface relevant information faster and interact with corporate actions data more efficiently.
These capabilities can improve the speed, consistency, and scalability of processing while also helping identify exceptions and support more intelligent workflows. Importantly, they are underpinned by our established validation processes and subject matter expertise, helping ensure that A.I. enhances the service without compromising the accuracy and controls our clients depend on.
Q: How is S&P Global exploring A.I.-driven changes to corporate actions workflows, and what role could agentic A.I. play in the evolution of its offerings?
A: We are already building agents that can scout for relevant information, store and organize it, and rapidly transform it into structured corporate actions data. Over time, these agents can support more connected workflows by monitoring information, interpreting changes, performing validations, identifying exceptions and orchestrating next steps across the processing lifecycle.
The opportunity is to automate more of the routine processing while directing complex or ambiguous cases to subject matter experts. We see the strongest model as one that combines A.I.-driven automation with human oversight, enabling greater speed and scalability while maintaining the accuracy, control and auditability that corporate actions processing requires.
Q: How would you characterize A.I.’s role in evolving corporate actions? Would you say it is a revolution?
A: I would describe it as evolutionary in adoption, but potentially transformational in impact. Corporate actions is an accuracy and control intensive business, so change will happen deliberately rather than overnight.
A.I. has the potential to fundamentally change how information is sourced, interpreted and transformed into actionable data. Domain and human expertise will remain critical, but the role of operations will evolve significantly. Rather than spending much of their time sourcing and chasing information, specialists will increasingly be able to focus on applying their expertise to readily available, intelligently extracted and curated data, resolving complexity and making higher value decisions.
That combination of A.I., trusted data, and human expertise has the potential to reshape corporate actions processing while preserving the accuracy and controls the market depends on.
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Interesting read, continuing the theme of improving the interpretation of unstructured corporate action data after publication.
As an industry, we do seem to have become so focussed on improving post-publication interpretation that we’ve stopped asking whether that’s where trust should first be established.
With technology now capable of creating structured representations of issuer intent, why not make it available to those responsible for issuing the event, allowing them to verify that the structured representation accurately reflects their intended business outcome before it is published to the market?