Matt Ashare
5 min read
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The banking industry was quick to recognize the business potential of generative AI and, on the flip side, appreciate the perils inherent in reckless adoption. Adept at managing risk, the sector’s largest institutions took a cautious yet persistent approach moving pilots into production.
Adoption has picked up momentum over the last year, according to Evident Insights, which tracks 50 of the largest banks in North America, Europe and Asia. The 50 banks announced 266 AI use cases as of last week, up from 167 in February, Colin Gilbert, VP of intelligence at Evident said Tuesday during a virtual roundtable hosted by the industry analyst firm.
“The vast majority, or about 75%, are still internal or employee facing,” he said, adding that the distribution between generative AI and traditional predictive AI use cases was split roughly 50/50.
As banking integrates the technology into daily operations and models mature, the mix is shifting toward generative AI capabilities with customer-facing features, Mudit Gupta, partner and Americas financial services consulting practice AI lead at EY, said during the panel.
“You tend to start with productivity because it’s low risk,” Gupta said. “You establish proof points so that when you get further down the road of adoption, you can move on to transformation.”
Technology executives from three global banks each put their own spin on Gupta’s formulation.
“We are taking incremental steps to do something exponential,” Rohit Dhawan, director of AI and advanced analytics at Lloyds Banking Group, said. The bank is consolidating its AI efforts to move beyond individual use cases after bolstering its cloud-based data strategy earlier this year with Oracle’s Azure-based database system and Exadata customer cloud data system.
“It’s a very different mindset where you go from thinking about how to infuse or optimize a process with AI to fundamentally reimagining the process with AI,” Dhawan said.
Generative AI use cases abound in banking. The technology has capabilities that reach across processes, from managing vast quantities of customer and compliance data for associates to assisting engineers in refactoring legacy applications.
Banking executives expect generative AI to be capable of handling up to 40% of daily tasks by the end of the year, according to an April KPMG report. Nearly 3 in 5 of the 200 U.S. bank executives surveyed by the firm said the technology is integral to their long-term innovation plans.
