Australia’s CommBank completes migration of data to AWS in AI drive

The Commonwealth Bank of Australia (CommBank) plans to accelerate the integration of artificial intelligence (AI) into its business after completing a year-long migration of its data platform to Amazon Web Services (AWS).

Its data platform will be integrated with every banking service channel and, through AI, will provide personalised services to customers.

For example, using AI in customer services enables chatbots and virtual assistants to provide 24-hour support, while personalised banking experiences can be built by analysing customer data. AI is also increasingly being used proactively, rather than reactively, anticipating customer needs rather than waiting for enquiries.

The project to move the data platform to AWS began in July 2024, supported by Indian IT services supplier HCLTech. More than 61,000 “data pipelines” were tested during the migration.

AI decisions

CommBank makes about 55 million decisions every day using AI, according to the bank’s lead for data platforms, Terri Sutherland.

We have over 2,000 AI models feeding on approximately 157 billion data points, making CommBank one of the largest corporate users of AI in Australia
Terri Sutherland, CommBank

“Migrating our data to the cloud is a significant milestone for the bank,” she said. “We have over 2,000 AI models feeding on approximately 157 billion data points, making CommBank one of the largest corporate users of AI in the country.”

Sutherland said moving all of the bank’s data to the cloud would allow it to simplify its technology stack, reduce the on-premise datacentre footprint and scale operations on demand.

“Having the right data foundations, built on advanced technology, enables CommBank to unleash its full potential with AI and agentic AI,” she added.

Jamie Simon, director of financial services at AWS in Australia and New Zealand, agreed. “This migration represents a significant milestone and provides the foundation for CommBank to accelerate the innovative use of AI and agentic AI to deliver better customer and employee experiences,” he said.

AI strategy

The use of AI in banking goes much deeper into organisations, with its application in areas such as risk assessment, fraud detection and process automation.

But recent research from Boston Consulting Group, presented in The AI reckoning in banking report, found that only 25% of global banks use AI strategically by embedding it in products, operations and customer engagement to strengthen competitive advantage.

“Most remain stuck in siloed pilots with no clear path to scale,” the report said.

It reported that one of the problems was the fact that most banks lack the infrastructure to scale AI. “Legacy systems, fragmented data and insufficient orchestration capabilities are blocking real-time, integrated AI applications. Fixing these gaps demands significant investment and executive-level commitment,” said the report.

In the UK, the Bank of England and the Financial Conduct Authority have been tracking how financial services firms in the UK are using AI and machine learning. The results of a survey of 120 firms found that three-quarters are already using some form of AI in their operations. This included all the large UK and international banks, insurers and asset managers that responded, and represented a 53% increase on the same survey in 2022.

The Bank of England survey found that 41% are using AI to optimise internal processes, while 26% are using AI to enhance customer support.

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