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Australian sectors
APRAASICOAICACCC

AI governance in Australian financial services.

Australian banks, insurers, super funds, and credit providers face overlapping AI obligations from at least four regulators. This is the complete map.

Your regulatory obligations at a glance

Nine frameworks. All active. Map your AI systems against each.

CPS 230
APRA

AI systems in material business activities are operational risks requiring documented management, testing, and oversight.

High
CPG 234
APRA

AI systems are information assets subject to information security standards, including third-party vendor assessments.

High
CPS 220
APRA

AI risk must be identified and managed within the enterprise risk management framework with board visibility.

High
Responsible Lending
ASIC

AI-driven credit assessment must comply with NCCP Act responsible lending obligations. Automation does not reduce liability.

High
Best Interests Duty
ASIC

AI-assisted financial advice and robo-advice systems must comply with Corporations Act Chapter 7 best interests duty.

High
RG 271 IDR
ASIC

AI-driven decisions are subject to Internal Dispute Resolution requirements — customers must have access to meaningful explanations.

Medium
APP 1, 3, 6, 11
OAIC

Privacy policy must address AI use. Customer data collection and use for AI must comply with original collection purpose.

High
Section 18 ACL
ACCC

AI-generated product representations must not be misleading. Dynamic pricing AI subject to unconscionable conduct provisions.

Medium
SIS Act s62
APRA

Superannuation funds: AI use of member data must be solely for the purpose of providing member retirement benefits.

High

Guidance for Australian financial services AI

Detailed analysis of every regulatory framework that applies.

Priority actions for financial services AI governance

Conduct a full AI system inventory — map every AI system to the applicable APRA, ASIC, OAIC, and ACCC obligations

Assess your model risk management framework — does it adequately cover ML models including explainability, drift monitoring, and distributional assumptions?

Review credit decisioning AI for responsible lending compliance — independent legal assessment of AI methodology is required

Audit your privacy policy — does it accurately describe AI use of customer data? APP 1 requires it

Establish customer explanation mechanisms for AI-driven adverse decisions (credit refusals, insurance denials, claim rejections)

For super funds: obtain legal advice on sole purpose test compliance for any AI that uses member data for purposes beyond direct member benefit

Brief your board on AI risk — APRA and ASIC both expect board-level awareness and oversight of material AI risk

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