Gresham combines advanced AI with deep financial data context, enabling firms to move from reactive data management to proactive and automated data operations.
Contextual AI for Enterprise Data Intelligence
Financial institutions today face an explosion of data sources, increasing regulatory pressure and complex vendor ecosystems. Data teams must ingest, compare and validate market and reference data from multiple providers while managing ongoing data quality issues and reconciliation breaks.
Gresham is addressing these challenges by embedding AI directly into enterprise data workflows. Built specifically for financial data environments, Gresham EDM will enable firms to automatically detect anomalies, compare vendor feeds, investigate data conflicts and resolve exceptions faster than ever before.
Through a conversational interface, users will interact directly with their data environment, asking questions such as:
Gresham is combining advanced AI with deep financial data context, enabling firms to move from reactive data management to proactive and automated data operations.
With AI embedded across the Gresham EDM platforms and operating seamlessly across capabilities, firms will benefit from enhanced enterprise data mastering, governance and reconciliation.
In today’s world of increased complexity resulting from increased variety and volume of data sources, regulation and market volatility, Enterprise Data Management teams can face several persistent common challenges:
Overcoming data complexity
Financial institutions consume data from multiple vendors and internal systems. These datasets frequently contain inconsistencies and conflicting information.
Reducing manual exception handling
Investigating data conflicts, validation failures and reconciliation breaks requires significant manual effort across multiple systems.
Improving data onboarding
Onboarding new vendor datasets can be heavy due to mapping, validation and governance requirements.
Visibility into data health
Firms without a strategic approach to Enterprise Data Management may struggle to gain a holistic view of their data quality and operational data environment. Resulting in data teams spending a disproportionate amount of time investigating issues rather than improving data quality and delivering business value.
Enhanced Data Governance
Expanding EDMs data governance capabilities beyond manual approaches for meta data management, lineage and user management to encompass AI machines and their auditability.
Introducing AI-Native Enterprise Data Management
Gresham is embedding contextual AI directly into enterprise data management workflows.
Instead of manually investigating issues, data teams can rely on AI to:
Transforming enterprise data management from a reactive operational function into an intelligent, automated system.
Why Gresham
Gresham is uniquely positioned combining AI with deep enterprise data management expertise.
Unlike generic AI tools, Gresham understands:
This enables Gresham to deliver context-aware intelligence specifically designed for financial institutions.
Gresham at the forefront of AI-Native Enterprise Data Management
Gresham has decades of experience delivering enterprise-grade solutions for data management, reconciliation and control environments. Gresham has amongst the largest R&D of any EDM provider. With multiple platforms and business solutions, it offers a right-sized approach across all business solutions and industry participants. Buy Sides, Sell Side, Corporates and Infrastructure Providers. Gresham can provide full scale Data Management as a Service.
Unlike generic AI providers, Gresham understands:
Gresham’s deep domain expertise enables EDM to deliver AI capabilities that are practical, accurate and aligned with real-world financial workflows. Click here to speak to an expert Contact Us | Gresham