ASIC
ASIC, the Financial Accountability Regime, and design and distribution obligations applied to AI in Australian financial services.
24 articles
Articles about ASIC
The Model Failed. Whose Bonus Moves?
CPS 511 already requires an APRA-regulated entity to set criteria that adjust variable remuneration downwards for a significant failure of risk management or significant adverse outcomes for customers. It never mentions artificial intelligence, and it does not need to. The gap sits in the entity file: an AI use case with no accountable person the remuneration committee can name.
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Your Contract Generator Scales the Clause. So Does the Penalty.
A model that drafts contracts reproduces the same term across all of them, and section 27 presumes a contract is standard form once that is alleged. Section 23 of the Australian Consumer Law treats every unfair term proposed as a separate contravention, and the fixed maximum for a body corporate doubled to $100,000,000 in March 2026. Here is the test, the onus, the arithmetic and the audit.
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Your Resilience Documents Pass. Your Exercise Might Not.
APRA and ASIC have released the notes from their June superannuation CEO roundtables. The line worth acting on is that participants said crisis exercises often reveal governance, delegation and communication issues that documentation alone may not surface. Here is how to design one for an operation that now contains agents.
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A Gate Your Customer Can Retry Is Not a Control
On 13 August 2026 ASIC published surveillance findings against nine named online brokers, including onboarding questionnaires that allowed repeated or unlimited attempts to pass. The same defect drew a $10 million penalty in March 2026. The design question generalises to every automated eligibility gate an organisation operates, and it gets sharper when the customer has an agent.
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Your AI Credit Score Is Not a Responsible Lending File.
A model can rank credit risk, reconcile application data and flag exceptions. It still cannot prove the inquiries, verification and customer-specific suitability assessment behind a lending decision. Build a customer-outcome file that preserves the evidence and the authorised human judgement.
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ASIC Asked for the File. Your AI Summary Is Not the Production.
An AI summary can help organise an ASIC request. It cannot replace responsive source records, settle the notice's scope or make a privilege claim. Build a request-to-source ledger that lets legal reviewers trace every request item to native material, exclusions, gaps and the human production decision.
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AI Can Sort the Breach Queue. It Cannot Stop the 30-Day Clock.
AI can assemble evidence, connect similar incidents and challenge a preliminary assessment. It cannot decide when your licensee knew enough, whether a breach is significant or whether a report is due. Build the breach workflow around the statutory clock, not the model.
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Your TMD Needs Customers Who Do Not Exist.
Synthetic personas can expose a target market that is too broad, a distribution condition that fails at the edge and a review trigger that never fires. Use counterfactual pairs as adversarial tests, and never mistake generated cases for evidence of real customer outcomes.
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Your GenAI Approval Needs an Expiry Trigger.
A GenAI approval records what passed on one date. It does not prove the live system still deserves approval. Build a living validation passport with explicit failure modes, change triggers, expiry and a human-controlled stop-use rule, and keep the four regulatory layers behind it separate.
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Do Not Put a Whistleblower Disclosure Into Your General AI Tool
A whistleblower disclosure is not ordinary case data. Section 1317AAE of the Corporations Act protects the discloser's identity and anything likely to identify them. Keep the raw account inside the protected whistleblower environment, and let AI assist only with a deliberately reduced control record that an authorised human has cleared for use.
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FAR Eased Up. Your AI Map Still Holds
ASIC and APRA are trimming FAR reporting from 16 June 2026. The accountability behind your AI use-case register has not moved. The practical change is what you actively maintain versus what you only produce on request.
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Agentic Trading and the Purpose Problem
In REP 835, ASIC published the gap in its own enforcement model: agentic trading systems are hard to assess through traditional notions of trader intent. Read as a hole in Australian law, that is imprecise. Our core prohibitions are drafted on effect, and the High Court has already said a sole or dominant purpose is not necessary. But purpose has not disappeared. It has moved to the people who deployed the system.
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Governing AI Agents Before the Consumer Data Right Lets Them Act
The Consumer Data Right is gaining write access. Once actions are designated, an accredited provider, or an AI agent behind it, could initiate payments and switch products on a consumer's instruction. The controls for agent-initiated actions are far cheaper to build now, before any money can move.
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Australia Will Not Pass an AI Act. You Are Still Regulated.
The National AI Plan settled the question every GRC team was waiting on. Australia will not pass a standalone AI Act. That is not a reprieve. It means AI is already regulated, spread across the laws and regulators you answer to now. Here is how to stop waiting for an AI law and map every AI use to the obligation it already touches.
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AI Wrote the Ad. ASIC Still Holds You to It.
ASIC refreshed its advertising guide for the first time since 2012, and it now reaches AI-generated advertising and the capability claims firms make about their AI-enabled tools. The medium is no defence. Here is what AI-washing looks like, what RG 234 now expects, and the marketing controls to put in place before the next campaign ships.
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AI in Complaints Handling: What RG 271 Reserves for a Person
Financial firms are putting AI into the exact process ASIC made enforceable in RG 271. AI can triage, summarise and draft a complaint response, but the 30 day clock, the reasons, the systemic issue call and the fairness of the outcome stay with a person. Here is the obligation map, a worked example and the prompts to build your own.
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The Scams Prevention Framework Meets AI: What 'Reasonable Steps' Now Demands
Treasury's exposure-draft codes for the Scams Prevention Framework set a technology-neutral reasonable-steps duty on banks, telcos and digital platforms. The scams it targets are now AI-generated, which raises the bar and creates a second duty: govern the detection AI you deploy to meet the first.
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Build an AI Use Case Register That Boards Can Actually Use
Practical guidance for GRC teams to create AI use case registers that deliver clear, decision-ready evidence for boards and risk committees.
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AI Cyber Risk Is Now a Board Governance Issue
ASIC's May 2026 cyber uplift warning highlights that AI-driven cyber risk demands active board and risk committee oversight, not just IT fixes. This article outlines a practical governance operating model for GRC teams.
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ASIC's AI Supervisory Posture, Decoded
ASIC's posture on AI in financial services is now visible across REP 798, the 2026 Key Issues Outlook, and recent statements from the Chair. Five themes shape supervisory expectation, and three create immediate work for compliance teams.
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FAR and AI: How Accountability Maps to Tooling Decisions
The Financial Accountability Regime makes specific senior executives answerable for the systems and decisions inside their portfolios. AI tooling decisions sit inside that accountability, whether they are formally documented in the accountability map or not.
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DDO and AI-Driven Personalisation: Where the Boundary Sits
AI personalisation is moving fast inside Australian financial services. The Design and Distribution Obligations were not written with adaptive recommendation engines in mind. The boundary between targeting and personal advice is the line GRC teams need to govern.
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APRA's Model Risk Thematic Review: What to Expect
APRA's AI supervisory work has moved from signal to substance. The April 2026 letter to industry reported a deep-dive on the largest banks, insurers and super trustees, and a forward plan of prudential reviews and thematic activities is being finalised. Where the pressure lands, and the work to do now.
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Australian AI Safety Standard: 18-Month Review
Eighteen months in, Australia's voluntary AI Safety Standard has shifted from optional reading to procurement table stakes. Three things worked. Two did not. The next phase is moving towards mandatory.
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