FCA Mills Review — Agentic AI, Accountability & The Perimeter Gap

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FCA Mills Review — Agentic AI, Accountability & The Perimeter Gap
FCA signals AI is no longer peripheral.

🟢 Why the Mills Review matters

FCA: “The Mills Review examines how autonomous artificial intelligence could increasingly reshape retail financial services and regulatory oversight.”

  • Delegated AI decision-making now part of sector operations.
  • Frontier-AI cyber capabilities + model concentration = system-wide risk.

FCA signals AI is no longer peripheral.

🟢 Consumer Duty — conduct anchor

FCA: “Existing frameworks are flexible enough… firms remain answerable for the outcomes their AI systems produce.”

  • AI-enabled services must still meet Consumer Duty outcomes.
  • Fraud, cyber-risk, consumer harm remain firm responsibility.
  • Frontier-AI safety depends on operational environment, not model hype.
  • Cyber-resilience review: “Models can generate large numbers of findings that are technically possible but difficult to validate, prioritise or act upon.”

Core risk: volume + autonomy > oversight.

🟢 SMCR — accountability does not move

SMCR — Senior Managers & Certification Regime — is the FCA’s accountability framework.

FCA: “Senior Managers remain responsible for the outcomes an AI system produces, even where behaviour depends on a third-party model provider.

Firms must:

  • Name accountable Senior Manager for each AI-driven process.
  • Define monitoring and escalation.
  • Maintain oversight even when model is external.

AI autonomy increases accountability density.

🟢 Operational resilience —governance must keep pace

  • Governance forums must understand model behaviour.
  • Escalation routes must be responsive.
  • Oversight must detect drift and degraded outcomes.
  • Concentration in cloud/model providers = system-wide risk.
  • Linked to critical third-party regime → future perimeter tightening.

🟢 The perimeter gap — general-purpose AI tools

FCA: General-purpose AI tools, such as ChatGPT, Claude or Gemini sit outside the FCA’s authorisation perimeter and create

  • Unregulated advice channels.
  • Consumer reliance with no protection.
  • Accountability ambiguity.
  • Cross-jurisdiction complexity.

FCA can warn but cannot regulate without international alignment.

🔴 Real-world perimeter gap — FT example

FT reports almost two-thirds of US doctors rely on searching OpenEvidence for patient decisions.

  • Mirrors FCA warning: unregulated AI influencing regulated outcomes.
  • Clinical and financial sectors share identical perimeter physics.
  • Accountability collapses when regulated decisions rely on tools outside the perimeter.

🟢 Checklist — regulated firms

  • Clearly accountable Senior Manager for each AI-driven process.
  • Defined escalation routes for abnormal AI behaviour.
  • Demonstrable human judgment over automated decisions.
  • Monitoring to catch drift before harm.
  • Guardrails, approval gates, permission limits.
  • Validation capacity matching AI autonomy.

Checklist — cryptoasset firms seeking authorisation

  • Consumer Duty applies once authorised.
  • Senior Managers must be named for each AI-driven process.
  • Governance + guardrails must be built into the application.
  • Consider interaction with unregulated general-purpose AI tools.

🔵 RACinform view

  • AI can act; firms remain accountable.
  • AI can decide; oversight must scale.
  • AI can discover; governance must keep pace.
  • The perimeter gap is already shaping clinical and financial outcomes.
  • International alignment will be required to close it.

Read more

The Adaptation Gap: Why Professional AI Awareness Doesn't Translate Into Daily Life

The Adaptation Gap: Why Professional AI Awareness Doesn't Translate Into Daily Life

🟢 Overview Many professionals can clearly identify AI risks inside their own domain while remaining largely unaware of similar risks in their personal lives. A dentist immediately understands: * Liability * Verification burden * Diagnostic risk * Accountability inside a clinical environment. The same person may use: * AI as entertainment * Recommendation algorithms * AI-generated content

By Vela Kuhaendran