Financial services firms face unique regulatory and real-time data demands that make data quality, security and accessibility the primary determinant of agentic AI outcomes rather than model sophistication. "It all starts with the data," according to Steve Mayzak of Elastic, as cited in the primary source. Gartner data shows over half of financial services teams have implemented or plan agentic AI, yet 57 percent of organizations per Forrester still lack internal capabilities for full leverage. Agentic systems amplify data weaknesses, requiring auditable, centralized stores that support deterministic outputs from non-deterministic models while handling unstructured natural language alongside structured transaction records. Primary coverage notes the need for speed, accuracy and governance but understates the scale of legacy silo fragmentation across historical bank formats and the deterministic consistency challenges in trade execution descriptions. Related analyses from Gartner reports on AI governance and Forrester studies on AI readiness highlight that incomplete indexing leads to lagged responses and untraceable decisions, patterns also observed in prior machine learning deployments in compliance monitoring.