What’s the Regulator’s Stance on AI in Financial Services?
AI offers exciting opportunities for financial services firms to increase productivity, automate decision-making, and better serve clients. But as tools become more powerful, Australian regulators are sounding a clear warning: governance, transparency, and data protection must evolve just as quickly.
From ASIC’s concerns about fairness, to AUSTRAC’s expectations around transparency, and APRA’s strict oversight under CPS 230, financial institutions must take a proactive approach to AI. Here’s what you need to know—and what to do next.
1. AI Governance: What Regulators Are Saying
ASIC – “Beware the Governance Gap”
ASIC’s 2024 REP 798 report warned that AI adoption is often outpacing governance. Key issues:
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50% of licensees had no policies addressing fairness or bias.
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Most did not inform customers about AI involvement in decision-making.
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Many had no audit or monitoring mechanisms for AI outputs.
Implication: If your firm uses AI (even indirectly), your policies, disclosures, and controls must keep pace—or risk non-compliance.
AUSTRAC – Transparency & Human Oversight
AUSTRAC released an AI Transparency Statement in February 2025, committing to:
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Responsible, ethical, and explainable AI use.
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Mandatory internal AI training.
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Human oversight of AI-generated decisions.
Implication: You’ll need to demonstrate the same transparency, especially when AI touches customer data, compliance, or financial crime systems.
APRA – Cautious Optimism, Strong Oversight
APRA has been conservative with its own AI adoption—but has made it clear that financial institutions must have risk and resilience measures in place before rolling out AI.
In particular, APRA’s new CPS 230 Prudential Standard on Operational Risk Management (effective 1 July 2025) requires:
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Identification and management of material service providers, including cloud-based or AI tool vendors.
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Business continuity and incident response planning for technology-related failures.
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Board oversight of operational resilience, including emerging technologies.
Implication: If your firm uses third-party AI providers (e.g. Salesforce Einstein, Microsoft Copilot, or ChatGPT integrations), you’ll need to assess and manage them under CPS 230 guidelines. Read our blog on CPS230 here.
2. Practical Actions for Financial Services Firms
Here’s how to stay ahead of regulatory expectations—and build trust with clients and boards alike.
✅ Understand the Types of AI You’re Using
Not all AI is equal in risk or complexity. Examples:
| Type of AI | Description | Examples in Financial Services |
|---|---|---|
| Predictive Analytics | Uses historical data to forecast outcomes | Lead scoring, churn prediction, investment risk modeling |
| Natural Language Processing | Interprets human language (text/speech) | Chatbots, email sorting, document summarisation |
| Machine Learning | Improves from data without explicit rules | Credit scoring models, fraud detection |
| Generative AI | Produces new content from training data | Report drafting, paraphrasing SOAs, marketing content creation |
What to do: Document all use cases, identify which types are in scope, and assess their level of risk—especially if they’re client-facing or decision-influencing.
📍 Know Where Your Data Is—and Where It’s Going
Data sovereignty and security are front-of-mind for regulators.
Checklist:
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Do you know the physical location of data processing and storage for your AI tools?
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Are data hosting regions aligned with your privacy obligations (e.g., Australian-hosted, ISO 27001 certified)?
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Are you using public tools (e.g., ChatGPT, Google Gemini) that could send sensitive data offshore?
Action: Review your contracts, privacy policies, and vendor agreements. Consider applying stricter controls around what data staff can use in public generative AI tools.
🔍 Update Your Governance and Risk Policies
If your Risk, Compliance, or IT policies don’t mention AI, they’re outdated.
Update to include:
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Clear AI ownership (who governs it internally?)
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How models are trained, validated, and monitored
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How often AI outputs are reviewed for bias, inaccuracy, or drift
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When and how clients are notified if AI is involved in decisions
🛠 Monitor and Assess AI Vendors Under CPS 230
AI capabilities are often bundled into the platforms you already use—like Microsoft 365, Salesforce, Xero, or workflow automation tools.
Under CPS 230, you must:
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Maintain a register of material service providers, including AI vendors
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Assess third-party AI for data handling, model transparency, and reliability
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Ensure you have exit strategies if a tool is no longer compliant or becomes high risk
Tip: Start asking providers:
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Where is the data processed and stored?
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How is model bias monitored?
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What governance frameworks exist for updates or training data changes?
🧠 Train and Educate Staff (and the Board)
AI isn’t just a tech issue—it’s a business issue. Regulators are increasingly expecting board and executive understanding of AI risks.
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Provide mandatory training for all users of AI tools
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Include AI governance in board and compliance updates
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Consider a “Responsible AI” checklist for every new implementation
Final Thoughts
AI can’t be ignored—but it also can’t be deployed without oversight. The regulators are clear: AI must be transparent, explainable, and aligned with existing laws and ethical expectations.
At Argo Logic, we work with financial services firms to help navigate the intersection of innovation and regulation. Whether you’re rolling out AI in Salesforce, implementing predictive analytics in Xero, or building custom integrations—our AI Readiness Audit, CPS 230 advisory, and implementation services ensure you’re building smart and staying compliant.
Want help understanding where your AI risk sits? [Reach out to our team].
