Big data helps banks with customer intimacy
The head of technology for ANZ Bank's institutional arm has said that big data will help the bank become intimate with the needs of its customers, in an age when those customers no longer want to spend a lot of time in meetings.
"One of the big shifts for us is the sale side of relationship management," Leslie Howatt, ANZ Bank's head of technology for institutional, Australia, said at an Australian Information Industry Association (AIIA) breakfast briefing this month.
"Our customers expect us to turn up fully understanding everything about their business, and with a value proposition for them that's already tailored, before you walk in the door."
Previously, the process had been that ANZ would have a few meetings with the customer to find out how their business worked and then come up with a plan. Now, Howatt said, the bank was expected to come to the table directly with a plan.
"We have an analytics group onshore and offshore, as well, to crunch a lot of that data; make sure that our teams can go out there with that information, up front," she said.
She said that the bank was achieving that with a combination of analytics products, services and smart people from within the bank.
John Minz, Heritage Bank chief executive officer, agreed.
"It's exceptionally important, I think, particularly for customer intimacy," he said.
"As we have less face-to-face interactions with our clients, it's very important to utilise the data which we have, to make sure we offer the right products and services to them."
"We're a bit fortunate as an industry, I think, that we do have large amounts of data."
Westpac CTO Jeff Jacobs, on the other hand, thought that, although customer intimacy was definitely a pertinent use of big data, fraud detection was one of the biggest areas for big data use in the bank, especially as technology developments had allowed the analysis to occur near real time.
Jacobs was the most fascinated by the unstructured data aspect of big data — the information available in sources that could not be stored in traditional data warehouses; for example, information in web logs.
"That's where the light went off for me, when I started looking at [big data]," he said. "It's amazing — some of the insights you can get from the unstructured data."