National Australia Bank is using two tools in Databricks’ AI ecosystem to create datasets that have multiple internal uses, and to “speed up analysts’ day jobs”.
NAB’s John Whiston.
The bank said in a statement that the Genie-branded tools are “now live within NAB’s analytics community”, with broader usage being explored.
Within the analytics domain, the Genie tools enable natural language querying of data, and save time building datasets for different purposes within the bank.
The embrace of Genie is a natural evolution for the bank, since its enterprise data platform Ada largely runs on a Databricks stack.
Speaking at the vendor’s Data+AI Summit in San Francisco, data and analytics executive John Whiston said that with 180 data sources now available through Ada, the bank is now focused on embedding data and insights into its decision-making.
“We are getting to a point where we’ve got a critical mass of data in there, and we can start to unlock the value,” he said.
“AI-accelerated analytics”, powered by the Genie tools, is one way that NAB intends to do that.
Genie, he said, is enabling the bank to “move a lot faster to deliver the things that we used to struggle to deliver quickly.”
“We’ve always delivered them safely, but it’s been very difficult to deliver them quickly.”
Whiston described an example of an executive wanting to do “some analysis and get some predictive forecasts of … calls about card disputes that are coming into our call centres.”
Assuming the data streams exist, Whiston said that building out the use case would typically require an iterative process with a member of the data team that could take weeks or months to architect so it performs in a controlled and secure manner.
“Everything’s getting slower and slower,” he said.
“This is why we need to change because it’s very difficult for humans to operate in these kinds of data environments, [and] it’s even more difficult for agents to operate in these data environments.”
The bank is using Genie Spaces – also known as Genie Rooms – to curate datasets and overlay them with a natural language chat interface that makes them easy to query.
Whiston said that Spaces is “democratising value” from the data in its Ada platform.
“We want to give the value that’s in that data to everybody [in the bank],” he said.
Whiston said that a “space” could be built on top of a transactional dataset that could serve multiple use cases simultaneously.
“If I can build a Genie room on top of that transactional data set, I can service my group economics team who want to know how the general economy is performing and who’s buying what.
“I can satisfy business bankers who are about to go out and talk to a dentist somewhere in Queensland, and they can find out how dentistry is performing in that general area.
“I can give it to retail bankers who need to know where the customer is spending in their local areas.
“So we can certainly get great power of data out to the bankers, out to internal people as quickly as we possibly can. That’s how we’re looking at Genie [Spaces].”
Analysts can also use the “pre-prepared Genie” Spaces to respond to ad hoc queries from the business faster.
The other Genie tool in use is Genie Code, which is an AI coding and data assistant for developers.
“My analysts are heavy users of that in terms of preparing queries a lot more promptly and efficiently,” Whiston said.
“That gives us a way to move with the speed, scale, safety, and simplicity that we’re looking for.”
Targeting customer experience improvement on dispute resolution
NAB said in a statement that one thing it wanted from its data holdings is “to better understand what customers need in key moments.”
This aligns with NAB’s broader strategy to be “relationship-led” and to “provide exceptional experiences for our customers,” Whiston said.
“If you think about what we need to be relationship-led, we need to know the context that our customers operate in.
“We need to know about them, we need to know their businesses, we need to know their markets, and we need to know what’s going on in the broader economy.
“We need to bring all that together so that when our bankers are in those moments with customers, they’re equipped with everything they need to be able to have deep and meaningful conversations.
“If we want to provide exceptional experiences, we have to be able to get that data to people as quickly as we can, as promptly as we can, and through an interface that they’re all happy to deal with.
“And if we want to be safe and resilient, we need to be able to get that in a secure environment that we can tightly control and that we can make sure nobody gets access to anything they’re not supposed to get access to.”
Genie Spaces provides that – and one of the specific uses of it so far has been to analyse customer disputes captured by a dataset built using call centre transcripts.
The dataset can be queried using natural language, and this has helped the bank to recognise issues that impact customer experience around dispute resolution, head of AI science Nitin Sachdeva told the Databricks Data+AI Summit.
“If I talk about the example of disputes, what we found was the insights that we’re generating from the data helped us to understand that customers who were calling multiple times were not calling because the dispute itself was complicated or fraudulent. It was because there was an inherent need by our customers to be informed in the process of dispute resolution,” he said.
“With Genie and LLMs, we were able to explore hundreds of other customer intents that were modelled on Databricks, on the unstructured transaction data, to understand where the ambiguity exists and use these insights to shape better notification or clear guidance and more proactive service interventions.
“So, using Genie and LLMs in our enterprise settings, we can reason across customer calls, their sentiments, resolution outcomes [and] any behavioural signals to identify what can be some of the avoidable contacts and what actions will have the greatest impact.
“The opportunity is bigger than just speeding up customer resolution. It’s about using data and AI to redesign the experience for our customers.”
In a statement, NAB specifically referenced “transaction disputes” as one of its areas of analysis and focus.
Executive for data and analytics Jessica Cuthbertson said the bank had shifted to more proactive information as the investigation progresses.
“This reduces uncertainty for customers and that’s important,” Cuthbertson said.
“We can see the difference it makes – customers who are proactively informed throughout the process are 30 percent less likely to call to get information or for peace of mind.”
Ry Crozier attended Databricks’ Data+AI Summit in San Francisco as a guest of Databricks.
