Transcription:
Penny Crosman (00:03):
Welcome to the American Banker Podcast, I'm Penny Crosman. At American Banker's Digital Banking Conference in Boca Raton in June, Editor-in-Chief Chana Schoenberger and I interviewed honorees of our Innovation of the Year award. First up, I spoke with Derek Waldron, chief analytics officer at JPMorganChase.
First interview:
Hi, I am Penny Crosman, technology editor at American Banker, and I am here with Derek Waldron, who is chief analytics officer at JPMorganChase. And our topic today is how banks can scale AI. JP Morgan is obviously a very large bank, and you have been deploying AI across the entire workplace. How many people are using it right now?
Derek Waldron (00:48):
So we started about 18 months ago rolling out our generative AI platform. I think that's what we'll speak about today. And over the course of 18 months, we've gone from zero to about 230,000 users across JPMorgan, which is a little over two thirds of the entire employee base using that tool today.
Penny Crosman (01:08):
How can you keep customer and bank data safe when you're using large language models across so much data and it's used by so many people?
Derek Waldron (01:19):
Yeah, I think that the safe use of LLM inside the enterprise is a very important topic, and it's important to think about both the enablement of the technology and then how it's used inside the enterprise with regards to enabling the technology. These days, LLMS can come into the enterprise into many, many channels. There's the big model providers like OpenAI and Anthropic. There are the cloud providers that offer solutions. There's SaaS that provides solutions. There's open source models, and each of these has different risks associated with IT, data security being one of them. So the most important thing to do is to be very aware and deliberate as to how the LLM technology is going to be enabled and bought into the enterprise. And that requires thinking very carefully about the data lineage, what happens to that data, make sure that it's not stored where it shouldn't be. Certainly make sure that models can't be trained on that. And once the enabler channels are determined, everything else should really be shut down. Once the technology is enabled, then there's a question as how it's being used as other considerations then for safe and appropriate use inside the enterprise.
Penny Crosman (02:42):
You mentioned not having models trained on your proprietary data, which I know is something all banks are interested in doing. How do you do that? Do you just tell the model builder, model operator not to do it? Or do you have to put a specific in place to protect your data?
Derek Waldron (03:01):
Yeah, these days many of the big model providers do have enterprise offerings, which have technology and contractual provisions to ensure that bank data is kept safe. In addition, cloud providers have enabled these types of models in their infrastructure. Of course, much bank data goes to enterprise cloud offerings today, we're used to using that. As long as the security is of the same level for an large language technology, I think banks can get very comfortable with that.
Penny Crosman (03:35):
Anthropic's CEO recently said that AI is going to kill 50% of white collar jobs. What did you think of that prediction?
Derek Waldron (03:45):
Yeah, without a doubt, the next generation of AI is going to have widespread workforce applications. But I think specifically how it plays out is quite unclear. It's not the first time in banking that we've had very disruptive types of technologies. Think about the mainframe or the ATM or the internet. All of these were speculated to have wide ramifications on the headcount base, yet we see that employee bases of banks just generally keep getting larger and larger and the cost income ratio is a little bit more efficient, but it hasn't played out quite the way that people thought it would. A great example is the ATM, which was thought to be eliminating branches, yet at JPMorganChase, 25 years after the ATM came out at scale, we have more branch bankers than we did back then, albeit they're doing different things than they were before.
Penny Crosman (04:43):
That's interesting analogy. And how do you use generative AI in your personal life?
Derek Waldron (04:49):
I try and be a power user of it in my personal life. I have young kids, so I use it to create stories for them. I use it to push my own thinking as my own coach, my own teacher, my own mentor. And increasingly over time I'm pushing the envelope of the things that I can do with it. A year and a half ago, this was very much just for synthesis summary and question and answer. Now I'm really using it as a thought partner to help me think through incomplete ideas to help become a real sort of sparring partner to push my thinking.
Penny Crosman (05:23):
All right. Well, Derek Waldron, thanks so much for joining us today.
Derek Waldron (05:27):
Thank you.
Penny Crosman (05:28):
Next, Chana Schoenberger interviewed David Rogstad, president of Starion Bank in North Dakota.
Chana Schoenberger (05:34):
Hi, I'm Chana Schoenberger. I'm the editor-in-chief of American Banker and I have with me here Dave Rogstad from Starion Bank in Bismarck, North Dakota, which is one of our Innovation of the Year winners. Welcome, by the way. Your team won in the category of embedded finance. So tell us a little bit about your project.
David Rogstad (05:55):
Well, thank you for the award and thank for having us here and I appreciate that. So our award is banking as a service. We took an underserved or underbanked community and we found a way to make banking work for them. We worked with a couple different corporate partners and they're able to, as gig workers, not only do their work through that app, they're also able to do their banking through the same app that they can get their jobs, their gig jobs from. So we are able to take that, give them full use of any banking service. So debit cards, ATM, they can do everything within their app right there.
Chana Schoenberger (06:37):
So are they getting a checking account and does it bear interest?
David Rogstad (06:43):
It doesn't bear interest. There is rewards with it though. So there's debit rewards and that kind of thing with it.
Chana Schoenberger (06:50):
What is a debit reward?
David Rogstad (06:52):
When you swipe your card with the interchange, you get so much for different activities and much like a credit card rewards.
Chana Schoenberger (06:59):
Huh. I didn't realize you could do that with a debit card. So that's brilliant. And can they also apply to get the more regular products with you, a savings account?
David Rogstad (07:11):
Not through that. So it's set up as essentially as a separate bank within our bank. So they can't directly apply through us outside of the normal channel. So now that they are part of Starion, they can go to Starion and they can apply online for a savings account or a checking account or a loan or anything like that. But as it's right now our initial steps, they cannot do any additional besides the debit account.
Chana Schoenberger (07:38):
And what happens if they leave the company? You said it was DoorDash, right? So if they no longer work there, do they get to keep their account or it just goes away?
David Rogstad (07:47):
Nope, their account will remain with them. So they can still have access to their account and they can still hold their funds there and do all that. So they have to be a part of it to sign up for the account initially, but they can always come back. They're contract workers, so they don't work on and off. They may work once and then they may not work again for another seven months or six months or something.
Chana Schoenberger (08:16):
But the money's not stuck, it belongs to those people.
David Rogstad (08:18):
It belongs to those people. Yep.
Chana Schoenberger (08:20):
Gotcha. Okay. So that's a really interesting application of baas. There's been a lot of sort of noise around baas. And then with the new administration, it looks like some of the regulations may be easing up a little bit. How did you get comfortable with the fintech partners that you chose?
David Rogstad (08:37):
It was really just trying to determine the right partners, those that understood. We have a third party that helps with a lot of the compliance issues and making sure we have a full team on staff to take care of that on their side of things. So we have program managers that take care of, we have a corporate sponsor that does the accounting side of everything and we use some really big experts in that field. And that's really where we wanted to make sure that we had it. You talk about banking as a service and with compliance regulation and all that, everybody's really trying to figure out that we're doing the right thing, we maintain doing the right thing. Nobody wants to face the regulators and them saying, oh, this isn't right. Nobody knows what the regulators want from you today fully, so. Right.
Chana Schoenberger (09:29):
And they're not going to tell you
David Rogstad (09:30):
They're not going to tell us until we do it wrong.
Chana Schoenberger (09:31):
Yeah, yeah. It's like the game Operation. Remember that game, if you hit the rail it goes,
David Rogstad (09:37):
But otherwise you keep going until you hit that rail. Right.
Chana Schoenberger (09:41):
So we covered extensively the Synapse bankruptcy last year, and it was sort of a depth charge for the baas industry. A lot of banks decided that they were going to get out of baas after that, that it was just too scary for them. They couldn't get comfortable with it. How did you guys figure that your ledgering is good, your risk management is good on all this?
David Rogstad (10:04):
Well, when you talk about Synapse and their decline in the dollars and everything like that, we manage our balance sheet a little bit differently.
Chana Schoenberger (10:14):
You actually know where the money is.
David Rogstad (10:15):
Yeah, we know where the money is. Well, for one thing, we know where the money is. That helps.
Chana Schoenberger (10:19):
That's good.
David Rogstad (10:19):
And we sell off some of it so we're not all just deploying it. So we're managing, especially in the first couple years here, so we know what is that steady dollar amount that we have within and what's it going to look like going forward.
Chana Schoenberger (10:36):
Great. Great. So what's next for you?
David Rogstad (10:39):
It's really looking at the product that we have, really looking at what we have, how can we make this better? There's additional opportunities when you work with fintech companies such as this one here, they're always thinking about the next thing. Banks move slow, so we want to make sure that we're doing it right. So it's really trying to be okay, what is the right way to do it and how can we do it when we're not going to get in trouble? And we can still make them happy because they want to be ahead of the game. And I think as a small community bank, we have that opportunity to work with them, to be able to be mobile. We can move things, we're swifter to action than larger banks are and do it the right way.
Chana Schoenberger (11:33):
Great. Great. Well thank you so much for coming in. I really appreciate it.
David Rogstad (11:36):
Well, thank you and I appreciate you, the American Banker, and this award.
Penny Crosman (11:46):
Though these two conversations were very different, both tell a story of a traditional bank doing something new with technology and seeing some early positive results.
Thank you for listening to the American Banker Podcast. I produced this episode with audio production by Wenwyst Jeanmarie and Anna Mintz. Special thanks this week to Chana Schoenberger, Derek Waldron and David Rogstad. Rate us, review us and subscribe to our content at www.americanbanker.com/subscribe. For American Banker, I'm Penny Crosman and thanks for listening.