Tag Archives: FCA

Integrating AI and LLMs into Regulated Financial Services Data Platforms

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.

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Foundational Architecture Decisions in a Financial Services Data Platform

This article defines a comprehensive architectural doctrine for modern Financial Services data platforms, separating precursor decisions (what must be true for trust and scale) from foundational decisions (how the platform behaves under regulation, time, and organisational pressure). It explains why ingestion maximalism, streaming-first eventual consistency, transactional processing at the edge, domain-first design, and freshness as a business contract are non-negotiable in FS. Through detailed narrative and explicit anti-patterns, it shows how these decisions preserve optionality, enable regulatory defensibility, support diverse communities, and prevent the systemic failure modes that quietly undermine large-scale financial data platforms.

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

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.

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Entity Resolution & Matching at Scale on the Bronze Layer

Entity resolution has become one of the hardest unsolved problems in modern UK Financial Services data platforms. This article sets out a Bronze-layer–anchored approach to resolving customers, accounts, and parties at scale using SCD2 as the temporal backbone. It explains how deterministic, fuzzy, and probabilistic matching techniques combine with blocking, clustering, and survivorship to produce persistent, auditable entity identities. By treating entity resolution as platform infrastructure rather than an application feature, firms can build defensible Customer 360 views, support point-in-time reconstruction, and meet growing FCA and PRA expectations.

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Handling Embedded XML/JSON Blobs to Audit-Grade SCD2 Bronze

Financial Services platforms routinely ingest XML and JSON embedded in opaque fields, creating tension between audit fidelity and analytical usability. This article presents a regulator-defensible approach to handling such payloads in the Bronze layer: landing raw data immutably, extracting only high-value attributes, applying attribute-level SCD2, and managing schema drift without data loss. Using hybrid flattening, temporal compaction, and disciplined lineage, banks can transform messy blobs into audit-grade Bronze assets while preserving point-in-time reconstruction and regulatory confidence.

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

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.

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