AI Data Governance for Scalable Compliance in Modern Banking
summary
Claims a cloud‑native unified AI data governance framework that runs as governance microservices and integrates with Kubernetes, with a metadata orchestration engine ingesting thousands of events/sec, an intelligent graph‑based lineage tracker, and a real‑time compliance monitor. Uses distributed storage (relational + graph), in‑memory caches for sub‑millisecond queries, attribute‑based access, field‑level encryption and tokenization. A global tier‑one bank rollout reports 68% faster model time‑to‑market, 70–75% lower audit prep time and 42% fewer risk events.
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chapters (9)
- 0:00Introduction and Context
- 0:53The Imperative of Modern Governance
- 2:15AI Evolution and Containerization in Banking
- 3:46Challenges with Traditional Governance Models
- 4:48Unified AI Data Governance Framework
- 6:23Metadata Management and Automation
- 7:40Security and Compliance Alignment
- 9:35Real-World Case Studies and Future Roadmap
- 11:18Conclusion and Final Thoughts
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