Expero helped Vanguard develop a corporate actions analysis solution that applies AI in a focused, practical way. Rather than treating AI as a generic overlay, the solution was designed around a narrow, high-value use case where accuracy, explainability and workflow fit were paramount.

The throughline was helping users move more efficiently from signal to understanding, with relevant context around what changed and why, to help portfolio management teams spend less time gathering and reconciling information and more time making decisions.

Core solution elements included:

• AI-enabled reasoning to support corporate actions analysis
• Proactive agentic monitoring for exceptions and changes
• Semantic and natural-language unification of relevant information sources
• Unified, customizable views for easier interpretation and action
• Human-in-the-loop oversight to support trust, validation and continuous refinement

Our Approach

Expero began with an in-depth discovery to better understand Vanguard’s users, workflows, source materials and accuracy requirements. This included user interviews, workflow mapping, AI experience design and data assessment, with a particular focus on identifying where AI could deliver meaningful value without compromising confidence in the output.

A critical part of the approach was narrowing the use case to one that was impactful and realistically supportable, not just intriguing. Accurate outputs were a critical priority. Expero therefore focused on a problem set where large language models (LLMs), deterministic logic and structured data could work together in a way that was testable and operationally credible.

The technical strategy combined:

• Data engineering to organize and connect relevant information
• Deterministic logic where consistency and rules were essential
• Large language models to interpret and summarize complex unstructured inputs
• Knowledge-graph architecture to improve contextual understanding
• Iterative review to refine prompts, outputs and decision support behavior
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Key Benefits

By applying AI to corporate actions, Vanguard and Expero quickly created early value in a narrow, focused area where better decision support can have an outsized operational impact. The initiative improved how teams analyze and respond to corporate actions while also generating useful insight into how AI and modernization can be scaled more broadly.

Benefits include:

• Greater efficiency in corporate actions analysis
• Enhanced accuracy and transparency in decision support
• Reduced manual overhead for monitoring and research
• Clearer decision trails and more contextualized information
• Increased organizational confidence in how AI can be applied in high-stakes workflows
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Takeaways

Vanguard’s corporate actions initiative shows how targeted AI solutions can create practical value when they are grounded in real workflows, supported by strong data foundations and developed with experts involved at every step of the process. Rather than pursuing AI for its own sake, Vanguard and Expero focused on a use case where the technology could meaningfully improve how users interpret information and make decisions.

That work now feeds a broader modernization effort across portfolio management. What began as a focused corporate actions solution is helping Vanguard shape a larger vision for more connected tools, less fragmented workflows and more intelligent decision support across the portfolio management experience. In that sense, the project stands as both a successful use case in its own right and a strategic foundation for what comes next.