AI Governance in Finance: When No One Can Explain Who Approved the Model's Decision
mikeflache · x · 2026-10-30
Dinis Guarda's long-form essay examines AI governance and compliance in financial services, where AI already shapes credit, insurance, suitability, fraud detection and compliance workflows — yet regulation still holds institutions accountable for model-made decisions.
A central case study: a 73-year-old widow asks her wealth app's AI assistant about reinvesting her late husband's pension. The fluent assistant recommends a structured product at 11pm, unseen by any human; six months later it has lost value and the compliance officer must navigate Consumer Duty, the SM&CR senior-manager accountability regime, and operational resilience rules simultaneously.
Key argument: governance cannot be reduced to policy documents. It requires clear ownership, risk classification, approval gates, explainability, monitoring and human accountability — machines provide speed and scale, but humans must judge, explain and take responsibility.
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