Financial institutions have invested heavily in data infrastructure, but existing solutions fall short. Data lakes store yesterday's data and can't deal with complex schemas. Workflow and CRM platforms orchestrate processes but don't unify the underlying data. The core AI challenge remains unsolved: getting the right data, to the right model, at the right time and in a compliant way.
AI in financial services is even more demanding. A unified data platform in Finserv requires:
- Accessing decades of transaction history in milliseconds, not seconds
- Delivering real-time relevance ranking (not just retrieval) for AI accuracy
- Spanning siloed systems without forcing a single schema
- Maintaining the audit trails, access controls, and compliance FSI requires
In this session, we'll explore:
- Why AI is forcing the unified data conversation now
- What distinguishes a unified data platform from a data lake or workflow platform
- Practical steps to move forward even in a complex legacy IT architecture with multiple schemas
