Australia’s Central Bank Adopts AI

In 2025, the Reserve Bank of Australia (RBA) introduced a suite of AI-driven systems to strengthen research and policymaking. Among them is RBAPubChat, an internal chatbot trained on more than 20,000 documents spanning four decades of the bank’s knowledge base. Alongside it, the RBA launched text analytics tools that process unstructured business liaison reports, turning qualitative feedback into measurable insights.

This marks a new chapter in how central banks can use technology to handle overwhelming data, while keeping humans firmly in charge of decisions.

Unlocking Four Decades of Knowledge with RBAPubChat

RBAPubChat is designed to act as the bank’s memory. Staff can type natural language questions and receive clear answers based on years of analytical reports, speeches, and policy papers. Instead of manually digging through archives, policymakers can instantly access the context they need.

This tool reduces time spent on background research and helps ensure that current debates are informed by past lessons. By making institutional knowledge easier to retrieve, the RBA is bridging the gap between history and today’s economic challenges.

Turning Conversations into Data: AI for Business Liaison Reports

For more than 25 years, the RBA has conducted regular interviews with businesses across Australia to understand conditions on the ground. These notes have always been valuable, but they were unstructured and difficult to analyse at scale.

The new text analytics system changes that. Using natural language processing, it organizes thousands of pages of liaison reports into searchable data. Analysts can tag content, extract numbers, and detect trends in real time. This means that feedback from firms on topics like wages, prices, or supply chains can now directly shape policy discussions with greater accuracy.

Building a Complete Picture with WHAM!

The Wealth, Housing and Asset Module (WHAM!) is another pillar of the RBA’s AI initiative. WHAM! combines data on housing markets, superannuation, and business ownership to give policymakers a detailed map of household and business finances. By unifying these datasets, the RBA gains a clearer understanding of how economic changes ripple through the system.

With WHAM!, the central bank can better monitor risks, such as how rising interest rates affect both household wealth and corporate investment. It strengthens the link between policy choices and their real-world consequences.

Why AI Matters for Australia’s Financial Future

The RBA is clear that AI will not replace human judgment. Instead, it acts as a powerful assistant, helping economists focus on strategy rather than data retrieval. With these tools, decisions can be based on broader evidence, faster analysis, and more precise insights.

For citizens, this means policies that respond more quickly to economic shifts, whether in inflation, employment, or housing. For businesses, it ensures that the RBA’s decisions reflect real-time feedback from the economy, building trust and predictability in the financial system.