Over a two-decade career in the financial industry, despite a few job changes, the sheer scale of the industry has kept Jason Strle coming back for more.
Strle spent nearly 13 years JPMorgan Chase and almost six years Wells Fargo. He has now been serving as chief information officer of Discover Financial Services for a little over a year. “Essentially any transaction or movement of money throughout the country will have one of these three companies on each end of that transaction,” he explains. Fortune.
He also believes that the financial sector has a great responsibility to ensure that technology works well. “There’s a banking industry where it’s really, really important for people to swipe their card at the register or at a restaurant,” Strle says. “They’re counting on you, aren’t they?”
Discover and other financial company players are also counting on the great benefits of generative artificial intelligence. Technology could add between 200 to 340 billion dollars in value annually, mainly due to productivity gains, according to McKinsey Global Institute estimates. But the industry has been quite cautious in putting the AI generation into production due to high regulatory constraints, fears over customer data protection and questions about high costs with unclear details on what should be the return on investment.
“There are a lot of tools out there that have a fixed cost that put a lot of pressure on us to understand the value,” says Strle. “There needs to be a better connection between spending and the ability to understand value.”
This interview has been edited and condensed for clarity.
Fortune: What made you join Discover in July 2023?
What really attracted me to Discover was this unique direct-to-consumer arrangement. When there are no branches, the dynamic of rolling things out is radically different, because we need to have consistency in how our products work digitally. There is momentum in the industry for players who have been around for a long time; trying to figure out how to be more direct to consumer, more digital and deliver great customer experiences. The discovery began there. By the nature of our organization, we’re going to be constantly looking at technology.
When CIOs join a new company, they often talk about changes they’ve made to the org chart or reevaluate vendor relationships. Have you made any bigger changes and, if so, why?
I generally take a very selective approach when it comes to making these reorganization changes. The major change we made was the creation of a customer success organization. We wanted to focus more on how the customer felt from their perspective when using our products and services, which span multiple systems supported by multiple teams.
Financial institutions are using generative AI in different ways. What has been your goal so far with this technology?
There is the autonomous interaction with the customer, which is the riskiest element of what we do. We need to be able to explain very clearly, through our policies and procedures, what these models are going to do, and they will do it in a way that is consistent and fair to the customer. (Then) there’s the human in the loop, where generative AI can help you do things. Call summarization (with generative AI) is currently in production and helps us ensure that agents who are human and doing their best benefit from this additional capability, which can help digest the flow of the conversation and can be used. for coaching, feedback and understanding customer sentiment.
Why is it so important to keep humans informed when deploying generative AI?
This is an emerging area of understanding how humans interact with AI. It’s so good and so powerful at what it does that it almost trains you to be less diligent. It’s a real dilemma. The better these tools get, even if we’re talking about humans in the circuit, there’s the risk that people will start to turn off their brains because it seems so good at what it does. And then the machine exploits the human at that point. This can lead to many unexpected consequences and risks.
Financial companies tend to favor “build” rather than “buy” when deploying technology. With generative AI, what do you think?
Right now, I think it’s difficult for us to take full advantage of commercially available products. We are very protective of our customers’ data and if that data leaves our ecosystem, it does so with a healthy, even unhealthy, level of paranoia about where it is going and how it is going to be used. Then you have to ask yourself: does this benefit this commercial product and potentially exploit the intellectual property that belongs to us as a company? And we help them develop a product that they can sell to more people.
How do you assess the progress the financial industry has made in generative AI compared to other industries?
I would probably describe it as the early phases of what will ultimately be a very robust tool. When you look at chat capabilities, there is so much risk in giving advice that may be harmful or might not be uniformly accessible to all of your customers. The other piece is really making sure that you can maintain tight controls over your data and your data governance, while still being able to leverage those tools.
This story was originally featured on Fortune.com