Insights

Plain-language explainers and comparisons on AI governance and compliance for regulated industries — SOC 2 vs HIPAA, NIST AI RMF vs ISO/IEC 42001, EU AI Act readiness, and more.

• SOC 2 vs HIPAA: what's the difference and which do you need? — SOC 2 is a voluntary attestation of your security controls; HIPAA is US law for protected health information. A clear comparison of what each is, who needs which, and how they overlap.
• NIST AI RMF vs ISO/IEC 42001: how the two AI governance frameworks compare — The NIST AI RMF is a voluntary US risk framework (Govern, Map, Measure, Manage); ISO/IEC 42001 is a certifiable AI management-system standard. How they differ and how to use them together.
• EU AI Act readiness for financial services: a practical overview — A practical readiness overview of the EU AI Act for banks, lenders, and insurers: risk tiers, why credit scoring is typically high-risk, core obligations, and a preparation checklist.
• SR 11-7 and AI/ML models: what model risk management requires — SR 11-7 is US supervisory guidance on model risk management for banks. What it requires — robust development, independent validation with effective challenge, and governance — and how it applies to AI/ML.
• ISO/IEC 42001 vs SOC 2: AI management system or security attestation? — SOC 2 attests that your security controls work; ISO/IEC 42001 certifies how you govern AI. A clear comparison of scope, output, and when AI vendors need one, the other, or both.
• AI bias in credit and lending: fair-lending risk and how to test for it — US credit decisions fall under ECOA and Regulation B. How AI/ML models create disparate treatment or disparate impact, how to test for bias, and why 'black box' models still owe specific adverse-action reasons.
• HIPAA vs HITRUST: the legal obligation vs the certifiable framework — HIPAA is US law you must follow; HITRUST CSF is a certifiable control framework that maps to HIPAA and more. How they relate and whether you need HITRUST.
• RAG vs fine-tuning: which approach for enterprise AI? — RAG supplies external context at inference; fine-tuning changes model weights. When to use each — and why many production systems combine both.
• EU AI Act vs GDPR: how they differ and where they overlap — GDPR governs personal data; the EU AI Act governs AI systems by risk tier. Where they overlap — automated decisions, DPIAs, high-risk AI — and why you often satisfy both.
• Model drift: what it is and how to monitor AI models in production — Model drift degrades AI performance over time. Data drift vs concept drift, how to monitor inputs, predictions, and accuracy, and why it's the 'ongoing monitoring' model-risk guidance expects.