This bank tested 90 AI applications before selecting the top 2 – resulting in customer service and productivity benefits

“We’re really working to make sure that we have the appropriate safeguards and protections in place for our overall applications,” says Michael Ruttledge, chief information officer at Citizens Financial.

The Rhode Island-based bank says it has taken a thoughtful approach to generative AI, including creating a steering committee to make sure employees don’t go crazy and develop their own projects. Two use cases for generative AI that Citizens Financial expects to be introduced this year include an enterprise search tool that helps customer service representatives answer questions and GitHub Copilot, developed by Microsoft and OpenAI to help improve the productivity of the company’s software engineers.

The vast majority of banking organizations are in production or have introduced use cases for generative AI, often focusing on customer engagement, risk and compliance, information technology and other support functions.

“Financial services is a technology-driven business,” says Neil Pardasani, managing director and senior partner at Boston Consulting Group. And while financial services is starting with many other sectors, he says the industry can also “be a little more careful in terms of making sure that it’s done right and that the use cases that go to market always have a human perspective.” ”

Much of the industry’s early successes came from adopting generative AI tools to help with customer service. “This is an easy place to introduce the business case because of the capabilities of the tools,” Pardasani says.

At Citizens Financial, a new generative artificial intelligence tool that helps customer representatives is not reaching customers directly because the bank wants to continue to test the answers provided and continues to pay attention to hallucinations, which are reactions whose AI model can generate misleading or misleading information. completely false. “We’re getting past these barriers, but we don’t feel like we’re ready to go direct to the customer yet,” Ruttledge says.

With major players such as Google and Amazon introducing AI solutions, as well as thousands of startups, Citizens Financial says it has taken a safe risk by leveraging the company’s existing relationships with Microsoft and Amazon Web Services – cloud service providers with with which the company cooperates as part of Citizens’ hybrid strategy, which also includes Amazon Web Services. “We were able to build on that because we had already installed a lot of the infrastructure,” Ruttledge says.

North American banks are leading the way in AI innovation, according to a recent report published by Evident Insights, which found that JPMorgan Chase, Capital One and Royal Bank of Canada are leading the way in AI innovation. Banks on the continent were responsible for more than 80% of all AI research published by the sector last year, while Capital One and Bank of America dominated the AI ​​patent landscape and were responsible for two-thirds of all patents filed in the 12-month period ending in June 2022

“We have a lot of foundations to build on,” says Prem Natarajan, chief scientist and head of enterprise data and artificial intelligence at Capital One. “We are in an excellent position to build on this history. But let’s be humble and recognize that this is an emerging technology now and, given its power, deserves respect for taking a test-and-learn approach first.”

Last month, Capital One announced a partnership with Columbia University and committed a $3 million investment to an artificial intelligence innovation center aimed at accelerating research, but responsibly. “This transformation will be very big and the benefits will be very big,” says Natarajan. “All right. They’ll be here for a while. So let’s take the time to think about it and get it right.”

Natarajan says Capital One’s approach is to understand the different use cases the company can explore using generative AI, and then determine what data it can control that feeds into the models. Based on this, Capital One is considering what it can structure to test and learn, as well as mitigate any unforeseen impacts.

“We want to deliberately take a human-in-the-loop approach to begin with, so that we never really fully reveal things to the outside world,” Natarajan says.

Visa recently unveiled three new AI-powered risk and fraud prevention tools for the payments company’s business customers. Last year, the company blocked $40 billion in fraud, almost double the previous year.

Visa says the new products will launch in the first half of 2024 and will include tools such as Visa Deep Authorization, a new risk assessment solution designed to better manage payments made in the absence of a physical card.

“We apply deep AI learning models and we have literally trained this model on millions and billions of transactions,” says Anthony Cahill, global head of value-added services at Visa. “Will we provide an informed view of what a good payment is, or is it actually a payment that requires closer scrutiny?”

Last year, Visa announced a $100 million venture capital fund for generative AI startups, and chief product and strategy officer Jack Forestell said that while much of generative AI “has so far focused on tasks and content creation, this technology will soon not only change the way we live and work, but it will also significantly change commerce in ways we need to understand.”

Mastercard has also invested deeply in fraud prevention, spending $7 billion on cybersecurity over the past five years, including purchasing new technology and developing artificial intelligence tools that help identify fraud. Mastercard has also invested in about 20 different startups to get a first look at emerging security tools the company may want to leverage to support future anti-fraud readiness.

“Security permeates our business, from the protection of the systems themselves to the new capabilities we provide to our customers,” says Ed McLaughlin, chief technology officer at Mastercard.

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