Board ReportingAI Governance
Board Reporting for AI Risk and Model Risk Committees
A practical design for AI risk reporting that helps boards and model risk committees see adoption, material risks, incidents, assurance, and remediation.
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Everything I've written on regulated AI
Educational articles on AI strategy, governance, audit readiness, model risk, and financial regulation across PRA, ECB, Federal Reserve, and SEC themes.
21
Articles published
Governance10 articles
Audit1 article
Model Risk3 articles
Regulation4 articles
Technology10 articles
Finance11 articles
Healthcare1 article
New articles published regularly
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Featured pieces for readers who want the substance before the summaries.
AI Governance
AI Strategy and Governance for Regulated Financial Institutions
A practical, board-friendly guide to AI ambition, risk appetite, ownership, controls, and evidence in regulated financial institutions.
Read moreAudit & Assurance
AI Audit Readiness: Evidence, Controls, Logs, and Human Oversight
A plain-language note on making AI systems easier to audit by designing evidence and human review into the workflow.
Read moreModel Risk
Model Risk Management for AI: PRA SS1/23 and US Supervisory Guidance
Educational research on model inventory, tiering, validation, monitoring, explainability, and effective challenge for AI systems.
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Filter by governance, audit, model risk, regulation, sector, or technology.
Governance2 articles
AI GovernanceStrategy
AI Strategy and Governance for Regulated Financial Institutions
A practical, board-friendly way to think about AI strategy, governance, accountability, and control in banks and regulated financial institutions.
Read articleAudit1 article
AuditAI Governance
AI Audit Readiness - Evidence, Controls, Logs, and Human Oversight
How to make AI systems easier to audit by designing evidence, control ownership, logging, and human oversight from the start.
Read articleModel Risk2 articles
Model RiskPRA
Model Risk Management for AI - PRA SS1/23 and US Supervisory Guidance
A practical view of how AI model risk can be governed using model inventory, tiering, validation, explainability, monitoring, and effective challenge.
Read articleModel RiskBanking
AI Model Inventory and Tiering for Banks
A practical blueprint for cataloguing AI use cases, assigning model risk tiers, and linking governance depth to business impact.
Read articleRegulation2 articles
SECAI Governance
SEC and AI - AI-Washing, Predictive Analytics, Conflicts, and Disclosure Risk
A practical look at the SEC's AI themes for financial firms, including misleading AI claims, predictive analytics, conflicts, disclosures, and governance.
Read articleECBAI Governance
ECB AI Supervision - Governance, GenAI, and Prudential Risk
What banks can learn from the ECB's focus on AI governance, generative AI, strategy, risk management, and supervisory control.
Read articleTechnology6 articles
RAGLLM Engineering
Production RAG — Beyond the Basics
Building retrieval-augmented generation systems that actually work in controlled settings — chunking strategy, reranking, governance, and hallucination control for enterprise conceptual conceptual deployments.
Read articleTuningRAG
Fine-Tuning vs RAG vs Prompting — Choosing the Right Approach
A practical decision framework for choosing between prompt engineering, retrieval-augmented generation, and fine-tuning for enterprise AI conceptual conceptual deployments in regulated industries.
Read articleAgentsAgentic AI
Agentic AI Design Patterns for Regulated Enterprises
How to architect AI agents that plan, reason, and act across enterprise workflows — with the governance controls that regulated industries demand.
Read articleRisk PlatformBanking
End-to-End AI Risk Platform Architecture
A reference blueprint for modern banking and finance risk platforms spanning data, AI/LLM pipelines, MLOps, governance, and decision serving.
Read articleRAGLLM Engineering
Enterprise RAG Architectures
Designing retrieval-augmented generation systems for reliability, governance, and production-aware intelligence at scale.
Read articleAgentic AIAutomation
The Rise of Agentic AI
Agentic AI is moving beyond simple automation into autonomous systems that execute multi-step business workflows.
Read articleFinance3 articles
TreasuryBanking
AI-Native Treasury Control Tower
Where and how to use AI in treasury for real-time liquidity, risk, and decisioning with governance-first controls.
Read articleAI AgentsBanking
AI Agents in Banking Operations
A reference blueprint for AI agents in banking with governance-first controls, faster investigation cycles, and auditable decisioning.
Read articleRiskGovernance
AI in Financial Risk Management
Applying AI to risk modeling requires governance-first architectures and transparent decision workflows.
Read articleEnterprise5 articles
EvaluationsLLM Engineering
LLM Evaluation in Production
How to build evaluation frameworks that catch failures before they reach users — metrics, harnesses, and continuous quality monitoring for enterprise LLM conceptual conceptual deployments.
Read articleGuard RailsLLM Engineering
Guardrails for Enterprise AI
Building input and output controls that keep AI systems safe, compliant, and within policy boundaries — for finance, banking, and NHS conceptual conceptual deployments.
Read articleLLM ChatArchitecture
Enterprise LLM Chat Interfaces
Building production-aware AI chat interfaces for regulated industries — authentication, audit trails, multi-model routing, session governance, and compliance-by-design.
Read articleWorkflowsAgentic AI
AI Workflows for Regulated Enterprises
How to design, orchestrate, and govern multi-step AI workflows across banking, healthcare, and healthcare operations — without breaking compliance.
Read articleTemplatesLLM Engineering
AI Prompt and Workflow Templates for Finance and Healthcare
Reference prompt patterns and reusable workflow templates for regulated AI conceptual conceptual deployments — covering governance analysis, clinical summarisation, risk reporting, and agentic task orchestration.
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