PRIVATE AI FOR FINANCIAL SERVICES IN MELBOURNE
Since APRA CPS 230 took effect in July 2025, cloud AI services used by financial firms may trigger material service provider classification — meaning formal risk assessments, oversight obligations, and APRA reporting. Deploying AI on-premises avoids this classification entirely. We build these systems for Melbourne accounting firms, wealth managers, and advisory teams who need AI capabilities without adding third-party compliance burden.
Financial services is the one industry where the regulatory landscape shifted recently and specifically. CPS 230 changed the calculus on cloud AI adoption. Before July 2025, a wealth manager could argue their ChatGPT usage was de minimis. That argument is harder to make now. On-premises AI removes the question entirely.
WHY FINANCIAL SERVICES NEEDS PRIVATE AI
APRA PRUDENTIAL REQUIREMENTS
CPS 234 requires APRA-regulated entities to maintain information security capabilities commensurate with threats to their information assets. When an analyst pastes client portfolio data into ChatGPT, that's an external data transfer the firm needs to assess, document, and manage under CPS 234. With on-premises AI, there's no external transfer to assess — the data stays on your server.
CLIENT FIDUCIARY OBLIGATIONS
Imagine telling a high-net-worth client that their financial data was processed by OpenAI to generate a summary report. Regardless of the technical safeguards, that's a trust conversation most wealth managers don't want to have. Fiduciary duties require acting in the client's best interest — and routing their sensitive financial information through a third-party AI platform is a hard position to defend.
OPERATIONAL RISK MANAGEMENT
CPS 230 (effective July 2025) requires firms to identify and manage material service provider risks. If your firm relies on ChatGPT or Copilot for daily workflows, that provider may need to be classified as a material service provider — triggering formal risk assessments, contractual requirements, and APRA oversight. Deploying AI on your own hardware eliminates this dependency and the associated compliance overhead.
FINANCIAL SERVICES USE CASES
RELEVANT AUSTRALIAN REGULATIONS
| Regulation | Relevance to AI Deployment |
|---|---|
| APRA CPS 234 | Information security requirements for APRA-regulated entities — applies to AI system security |
| APRA CPS 230 | Operational risk management — requires assessment of third party service provider risks |
| Privacy Act 1988 | Governs handling of personal financial information under APPs |
| ASIC Licence Obligations | Operational resilience and client data protection requirements for licensees |
HOW THIS WORKS IN PRACTICE
A Melbourne wealth management firm with three offices needed their compliance team to search across eight years of regulatory correspondence, internal policies, and client reporting templates. The existing approach was manual: open the shared drive, guess which folder, read through documents until you found the right paragraph.
We deployed an on-premises AI search system that indexed over 12,000 documents. The compliance team can now ask natural-language questions like "What did we commit to regarding CPS 234 access controls?" and get answers with direct citations to the source document and paragraph.
Preparation time for their next APRA review dropped significantly. More importantly, the system runs on the firm's own server — no client data or regulatory correspondence reaches a third-party platform.
Representative engagement — details adjusted for confidentiality
"Before CPS 230, a wealth manager could argue their ChatGPT usage was de minimis and didn't need formal oversight. That argument is much harder to make now. The simplest compliance strategy is to remove the external dependency entirely — run the AI on your own hardware and the material service provider question goes away."
PRIVATE AI FOR FINANCIAL SERVICES IN AUSTRALIA
Read our complete guide covering APRA CPS 234, CPS 230, ASIC obligations, fiduciary duties, and practical use cases for financial services firms.
Read the full guide →FREQUENTLY ASKED QUESTIONS
How does private AI support APRA compliance for financial services?
By keeping all data processing on your own infrastructure, you avoid classifying a cloud AI vendor as a material service provider under CPS 230 — which would trigger formal risk assessments, oversight obligations, and APRA reporting. The system also supports CPS 234 requirements because there are no external data transfers to third-party AI platforms. Your information assets stay under your control, and the audit trail is entirely local.
What financial documents can be analysed with private AI?
We typically index client financial records, internal reports, compliance documentation, policy and procedure manuals, risk assessments, audit working papers, and regulatory correspondence. The system handles PDFs, Word documents, Excel files, and plain text. A compliance officer can ask a natural-language question like 'What are our obligations under the updated AML/CTF rules?' and get an answer with citations to the specific internal documents.
Is local LLM deployment suitable for wealth management firms?
Absolutely. Wealth management firms hold sensitive client financial information subject to fiduciary duties. If a client learned their portfolio data was being processed on OpenAI's servers to generate a summary report, that's a trust problem — regardless of what the privacy policy says. On-premises deployment removes that risk entirely. The AI runs on your hardware, and client data never touches an external platform.
How does AIRGAP LLM handle ASIC regulatory requirements?
ASIC doesn't mandate a specific AI deployment model, but it requires financial services licensees to manage operational risks effectively. A local deployment reduces third-party dependency risk — if OpenAI has an outage or changes its terms, your AI still works. It also gives you full auditability: every query, every document retrieved, every response generated is logged on your system. That's a much easier conversation with ASIC than explaining how you're managing risks with a US-based AI vendor.
Can private AI help with regulatory reporting?
Yes — particularly with the research and preparation side. The system can search your compliance documentation, surface relevant policy sections, and summarise regulatory requirements to support reporting workflows. For example, when preparing for an APRA review, your team can quickly pull up every internal policy related to CPS 234 information security controls. All processing stays on your infrastructure, so sensitive regulatory data never leaves your network.
Want to See How This Works for Your Firm?
We'll walk you through a deployment that fits your setup — your documents, your infrastructure, your compliance requirements. No sales pitch.
Request a Consultation →Or email us directly at hello@airgapllm.com.au