Sibos 2022: simplicity, AI & guarantees

Machine learning and artificial intelligence loom as the next step in bank guarantees – and beyond that, the tech could benefit a wide range of processes in financial services, helping banks and their customers.

Speaking to Institutional Insights, ANZ’s Head of Guarantees Product Sally Robinson said ultimately, guarantee instruments were relatively simple legal documents that lend themselves to the benefits machine learning can provide – including speed and increased productivity.

“As part of our regular guarantees process at ANZ, we analyse the text to ensure it meets a set of requirements,” Robinson said. “What we're looking at is: is there an artificial intelligence solution out there that could improve our reading of those documents, and improve our digital capability?”

This could be applied not only to new guarantees as they are processed, but - with the right permissions – past guarantees done by the bank, allowing for insights into historical trends across more than 20 regions that will help improve the process for ANZ and its customers.

Produced regularly, such data could also shed light on developing risks which can be addressed faster than through manual processing only.

“We're quite good at this kind of thing in the bank around credit risk,” she said. “But we've never done it with legal documentation. This is quite new.

“There’s a lot of value there even before you consider how the applicability could extend beyond guarantees.”

Replicable

Hari Janakiraman, Head of Industry and Innovation, Transaction Banking at ANZ said if the technology can be pinned down into something “replicable across the organisation, then you can set up an infrastructure so that it can be done at scale”.

“That provides a benefit not just to customers using guarantee products, but all the way to facility documentation, in terms of speeding up the process,” he said. “In some cases those documents are hundreds of pages long, and take time for our legal teams from all parties to review.

“You will see many use cases emerge if you  can help speed up the process by using machine learning. Of course, we need to first solve the immediate guarantee use case first.”

Simplicity

For customers, the overwhelming benefit of AI in guarantees will be the simplicity such tech will bring to the process, according to Robinson.

“Hopefully it'll be a pathway to simplicity, so we get quicker at assessing guarantees,” she said.

“If we can tie the technology into our exception-management tools, we can actually date stamp the whole event of issuing a guarantee.”

That allows groups like ANZ to use to the data to drive gains in service levels, time to market, and efficiency, Robinson said.

“It also creates opportunities for our teams to engage in more productive and higher-value work, as we know this lifts engagement internally and ultimately benefits customers,” she said.