In October, Citi announced that it joined forces with Google Cloud to support Citi's digital strategy through cloud technology. The FR’s chief research officer Dan Latimore caught up with Zac Maufe, global head of regulated industries at Google Cloud, and Rohit Bhat, Google Cloud’s managing director of financial services, to learn more about the partnership. 

What are the drivers of Citi’s significant announcement?
Rohit Bhat: As Citi thinks about infrastructure modernization, it clearly wants to prioritize safety and soundness while simultaneously enhancing both client and employee experiences through cloud technology and AI. By working with Google Cloud, Citi accomplishes three interrelated strategic goals:

1. Laying out a path to modernization that will be achieved with more speed and certainty than had they done it on their own.

2. Enabling platforms across the bank with  our Vertex AI platform to fuel its generative AI initiatives. One big goal with these initiatives is to boost employee productivity through the reduction of manual processes. Key use cases include improving developer efficiency and increasing knowledge workers’ speed by empowering them to sift through immense volumes of data to generate useful insights.

3. Improving the user experience for both customers and employees, including the ability to offer improved digital products, streamline employee workflows, and run high -performance computing (HPC) and analytics platforms. 

What are some specific examples of productivity improvements that you see in a banking context?

Zac Maufe: Let’s take a developer first [approach]. If you think about how much time they spend wrangling data versus analyzing it, today’s proportion is completely out of whack. Google Cloud’s Vertex AI platform combined with our data technology flips that equation on its head so that financial institutions can spend more time creating value. Another big area for banks will be updating legacy code and languages. When you consider that many of the largest banks still run on mainframes, there’s a huge opportunity for modernization if you can get off Cobol. Banks are increasingly looking to Google Cloud to securely move to the cloud, modernize their apps, and bring data silos together. 

For a knowledge worker on the business side, whether a banker, a fraud analyst, or a risk specialist, they too can use the technology to focus on the areas where they really add value, rather than trying to gather information and put it into a format where they can conduct meaningful analysis. Not only that, they also have access to much more data than before.

And then if you think about cloud’s progression of sweet spots—from infrastructure, to data, to  AI— building on each other, we’re now at the AI stage, which means that building on a solid foundation infrastructure and data, we can start to change business processes in a meaningful way, rather than just making outdated processes more efficient.

This technology has gotten a huge stamp of approval with the likes of Citi embracing it; what observations do you have for other banks who are considering their next steps in cloud and AI?

Zac Maufe: I’d make three comments on this.

First, banking is a regulated industry and you’ve got to have your regulators on board every step of the way. At Google Cloud, we spend an immense amount of time with regulators and we’ve clearly gotten them comfortable with our approach to deploying gen AI technology in a safe and secure manner. 

Second, banks typically have a human in the loop for many of these processes. This approach helps banks gradually integrate generative AI while maintaining human control, building confidence in the technology's reliability and fostering acceptance among employees and customers alike.

Third and finally, I’d emphasize that we’re getting to the point where the banks that have done the hard work of getting their infrastructure in place, and then have gotten their data into reasonable shape, are going to be able to realize immense benefits from cloud and AI. In fact, we recently published some research on this that found that early adopters of gen AI in financial institutions are already reaping significant rewards. For example, those who have moved gen AI use cases into production, 90% of those running gen AI in production and experiencing revenue growth due to gen AI initiatives are reporting revenue gains of 6% or more. Here’s the full report.