Westpac has built an “Intelligence Layer” that it will make accessible to the entire bank over the next year.
The “intelligence layer” appears to be an enterprise-wide data and AI platform.
iTnews understands it was built in-house, and has some integrations to Azure and Snowflake.
Chief executive Anthony Miller cited the “Westpac Intelligence Layer” as an example of the “enterprise-wide mindset” that the bank is taking with AI adoption.
A spokesperson for the bank has been contacted for comment on the technical architecture and foundations.
“We’re moving at pace and recently launched the Westpac intelligence layer, which draws on the enormous data and insights across the company to drive faster, safer and more proactive decisions,” Miller said at the bank’s annual results.
“We have prioritised using the layer in consumer to support our focus on growing proprietary lending. It is already giving our home finance managers better insights to deliver faster, more personalised service.
“I’m really excited about what we will achieve as we broaden this intelligence layer and roll it out across the bank in the next 12 months”.
In an accompanying slide deck, Westpac said the intelligence layer brings together data from 251 systems into a single place.
The layer is also where bank staff can deploy AI models to try to understand and “anticipate” customers’ needs; and access “conversational intelligence support”.
Miller said that AI “represents a significant opportunity” for the bank “to improve the way our people work as well as the quality of their work, to help us provide better, more consistent service to our customers”.
“We’re embracing new generative and agentic AI capabilities while also continuing to use traditional AI tools like machine learning and advanced analytics,” he said.
“These are helping us automate tasks and modernise our technology.
“It’s also giving our people more time back and providing bankers with more insights to serve customers better”.
Miller said the bank is focused on scaling “proven solutions” in the AI and data space.
Some of the benefits it is chasing include “stronger defences against fraud and scams, support [for] faster approvals for mortgages and business loans, help [for] employees quickly answer process and policy questions, and automated coding and testing”.
