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TD Bank adopts a single, trusted source of truth for AI analytics with Strategy Mosaic
TD Bank’s Transformation at a Glance
Established a governed semantic layer designed to support consistent AI adoption across teams and systems.
Broke down data silos by creating a shared semantic foundation while preserving autonomy across business teams.
Accelerated Strategy Mosaic deployment by extending the governance framework already established with Google Cloud.
The Challenge: Scaling AI Across Siloed Data Environments
TD Securities faced a challenge familiar to many capital market leaders: siloed data environments spread across multiple teams and technologies. Its trading desks, quant teams, and business groups had spent years building sophisticated data models and trading strategies. Each team operated with deep expertise in its specific business area, maintaining ownership of its data, workflows, and analytical approaches.
But that expertise, logic, and business context often remained isolated within individual groups. The autonomy that enabled innovation also contributed to technology sprawl and data silos, making it more difficult to consistently share data, insights, and business logic across teams.
As TD expanded its use of Google Cloud and accelerated its AI ambitions, it needed a governed foundation that could unify data across the organization while preserving the flexibility teams relied on to innovate.
The Strategy: Unifying Data and Governance for Enterprise AI
The Foundation
TD Bank built its architecture on Google Cloud, while Strategy Mosaic's universal semantic layer established a governed foundation for trusted business definitions across the organization.
The Solution
This created a consistent framework for critical enterprise metrics such as VWAP (volume-weighted average price), helping ensure that business definitions remain accurate and reliable across reporting, analytics, and emerging AI use cases.
The Differentiation
Strategy Mosaic allows TD Bank to scale governance without sacrificing autonomy. Teams can continue building specialized analytics and strategies while operating from a shared semantic foundation.
The Application
With a shared semantic foundation in place, TD Bank is positioned to scale AI initiatives across strategic growth areas, including transaction banking, electronic trading, and client-facing analytics.
Accelerating Enterprise AI with Trusted Data
By combining trusted business definitions with governed data access, TD Bank is building the foundation required to scale AI initiatives across the enterprise while maintaining the consistency and trust demanded in a regulated environment.
The Impact
TD Bank can now extend AI capabilities across business functions while maintaining the accuracy and reliability required in a highly regulated industry.
The Future
TD Bank is exploring AI-driven, agent-assisted claims processing within its insurance business, demonstrating how intelligent systems can help employees access insights faster and make more informed decisions.
The Long-Term Vision
Looking ahead, TD Bank envisions a future where intelligent agents help employees spend less time on routine tasks and more time strengthening client relationships.
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