FAQ

What are the three different uses of AI in compliance and supervision?

ASIC’s regulatory approach means AFS licensees should distinguish three uses of AI in compliance and supervision: AI as a coverage tool, AI as a pattern-detection tool, and AI as a substitute for governance judgement. The first two support monitoring when appropriately governed; the third does not replace accountable human judgement.

Expanded Answer

AI as a coverage tool allows an AFS licensee to review larger populations of advice files, file notes and supporting data than conventional human monitoring. Broader coverage can identify missing information, inconsistencies and defined exceptions. However, AI only assesses the information available to it. Broader coverage does not mean complete risk visibility.

AI as a pattern-detection tool examines information across multiple files, advisers, clients or periods. It can identify recurring advice deficiencies, unusual product concentrations, complaint clusters and other indicators that warrant investigation. This use moves supervision beyond isolated file findings towards identifying potential systemic or recurring conduct risks.

AI as a substitute for governance judgement is different. Automated analysis does not remove the need for investigation, professional judgement and accountable oversight. AI outputs depend on the underlying data, models, rules and assumptions. The practical rule is clear: use AI to extend visibility and identify patterns, not to outsource accountability. See the guide for advisers and licensees navigating AI in financial services.

Why it matters

Poorly governed AI can create false confidence in compliance systems. AFS licensees remain accountable for supervision, risk management and compliant outcomes. Increased monitoring coverage does not protect a licensee if automated findings are inaccurate, incomplete or accepted without appropriate human challenge.

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Practical guidance

  • Use AI to increase monitoring coverage while retaining human review of material findings.
  • Configure AI to identify patterns across advice, conduct, complaints and client outcomes.
  • Require accountable people to investigate, challenge and decide what AI-generated findings mean.

Further reading

AI in financial advice: efficiency gains, compliance risks and cognitive costs

The hidden risks of AI: ASIC’s review of licensees’ embrace of artificial intelligence

Why AI won’t fix your advice business

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