Tag Archives: SMCR

Integrating AI and LLMs into Regulated Financial Services Data Platforms

Leave a Reply

How AI fits into Bronze/Silver/Gold without breaking lineage, PIT, or SMCR: This article sets out a regulator-defensible approach to integrating AI and LLMs into UK Financial Services data platforms (structurally accurate for 2025/2026). It argues that AI must operate as a governed consumer and orchestrator of a temporal medallion architecture, not a parallel system. By defining four permitted integration patterns, PIT-aware RAG, controlled Bronze embeddings, anonymised fine-tuning, and agentic orchestration, it shows how to preserve lineage, point-in-time truth, and SMCR accountability while enabling practical AI use under PRA/FCA scrutiny.

Continue reading →

Golden-Source Resolution, Multi-Source Precedence, and Regulatory Point-in-Time Reporting on SCD2 Bronze

Leave a Reply

Why Deterministic Precedence Is the Line Between “Data Platform” and “Regulatory Liability”. Modern UK Financial Services organisations ingest customer, account, and product data from 5–20 different systems of record, each holding overlapping and often conflicting truth. Delivering a reliable “Customer 360” or “Account 360” requires deterministic, audit-defensible precedence rules, survivorship logic, temporal correction workflows, and regulatory point-in-time (PIT) reconstructions: all operating on an SCD2 Bronze layer. This article explains how mature banks resolve multi-source conflicts, maintain lineage, rebalance history when higher-precedence data arrives late, and produce FCA/PRA-ready temporal truth. It describes the real patterns used in Tier-1 institutions, and the architectural techniques required to make them deterministic, scalable, and regulator-defensible.

Continue reading →

Using SCD2 in the Bronze Layer with a Non-SCD2 Silver Layer: A Modern Data Architecture Pattern for UK Financial Services

Leave a Reply

UK Financial Services firms increasingly implement SCD2 history in the Bronze layer while providing simplified, non-SCD2 current-state views in the Silver layer. This pattern preserves full historical auditability for FCA/PRA compliance and regulatory forensics, while delivering cleaner, faster, easier-to-use datasets for analytics, BI, and data science. It separates “truth” from “insight,” improves governance, supports Data Mesh models, reduces duplicated logic, and enables deterministic rebuilds across the lakehouse. In regulated UK Financial Services today, it is the only pattern I have seen that satisfies the full, real-world constraint set with no material trade-offs.

Continue reading →