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DatabricksKim Hatton, Andrea DeSosa5 min readintermediate

Modernizing the Trade Lifecycle With Governed Data and AI

Read on databricks.com

Summary

Databricks argues that modernizing the trade lifecycle now hinges on building a governed, real‑time data foundation that spans research, trading, risk, ops and compliance, rather than isolated AI pilots. Starting with a few high‑value questions—execution cost, shock risk, exception rates—and using Unity Catalog and Agent Bricks lets firms achieve measurable speed and auditability gains before sca…

  • Connect research, trading, risk, ops, and compliance on a single governed data foundation to avoid fragmented views.
  • Prioritize high‑value workflows (execution cost analysis, shock risk, exception rates) before large‑scale migration.
  • Use signals like T+1 settlement, auditability demands, and shadow‑AI risk to trigger modernization.
  • Leverage Unity Catalog for centralized data/AI governance and Agent Bricks for domain‑specific AI agents.

Data and AI leaders in capital‑markets firms should care because governed data is the prerequisite for reliable AI‑driven trading decisions and regulatory compliance.

5/10
aigovernancedatatradingcapital markets

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