Stablecoins, Celebrities, and the Kardashian Effect on Banking

Hey everybody. Welcome back to another episode of What’s Going On in Banking. I’m Ron Shevlin, chief research officer at Cornerstone Advisors, and I’m here, of course, with my colleague Stacey Bryant. We’ve got some strong topics lined up today, and at the top of that list is artificial intelligence.

Stacey, I know you’ve been chomping at the bit to share some of what you’ve been seeing and hearing. What’s going on out there?

What’s going on, Ron?

I’ve been traveling. I just got back from the Virginia Bankers Association and Maryland Bankers Association joint convention down in Naples, Florida. It was beautiful, and it was nice to get away from the humidity in the New York City and New Jersey area.

I want to start with AI and then segue into a quote I saw on LinkedIn the other day. AI is coming fast, and for community banks, it can feel like another technology wave crashing into business models that have already been tested by multiple generations of “innovation.”

Ron, we had a conversation the other day about AI and the chat you had with our interns. You showed me a simple curve that made me rethink the way I look at AI and how I guide community-banking clients through the AI conversation.

You basically showed a technology evolution from PCs to the internet, mobile, cloud, and now AI. What did you call that curve?

I called it the productivity curve.

The point I’ve been trying to make to community-based financial institutions is that this is not as much of a revolution as people think. From a productivity perspective, it’s much more of an evolution.

About 45 years ago, PCs started appearing on people’s desks. Government economists had a hard time measuring the productivity impact, but turn those PCs off and see how much work gets done. They created enormous productivity gains, even though those gains weren’t always easy to quantify.

Then the internet took off in the mid- to late 1990s and connected people to dramatically more information. That created another large productivity boost.

Then the iPhone launched and kicked off the mobile revolution. Over the last decade, cloud computing became mainstream. All of those shifts laid the groundwork for us to benefit from technologies that fall under the AI umbrella, including machine learning, generative AI, and now agentic AI.

So from a productivity perspective, this is an evolution built on decades of technology adoption, not something that appeared out of nowhere.

That framing really changed how I looked at it.

At the bankers conference I attended, we came out of a breakout session where a college professor showed a similar timeline. As we were walking out, one of the bankers joked, “Bless the hearts of the people who have to think about an AI strategy in banking today. I’ll be long gone by then.”

The day before, our colleague Jen Wagner and I had presented on becoming a smarter bank by using AI and other technology. The room was standing-room only. You would have been proud.

To me, that says something important. Despite the fear around AI, people are becoming increasingly curious about frameworks that can help them stay relevant and innovative in a very competitive environment.

Our goal was to nudge bankers toward realistic ways to introduce AI one pain point at a time. That could mean chatbots, machine learning for fraud analysis, or other use cases. The important point is that these tools can be added incrementally as part of a strategy. You don’t need the budget of JPMorgan, SoFi, or Amazon to begin.

That brings me to a LinkedIn post I saw from Karan Kapur, the founder of a company that provides conversational AI for financial institutions.

His point was that people generally agree AI will be transformative, but we are underestimating the speed of change. Things that were not enterprise-feasible very long ago because of cost, resources, quality, latency, or other limitations are becoming viable in remarkably short periods of time.

He referenced the idea that exponential growth looks deceptively flat at first and then becomes sudden and overwhelming. His argument was that the cost of doing nothing, or creating self-inflicted delays, could become existential.

That’s a mouthful, but what do you think about the rate of change? Are financial institutions underestimating how quickly this is moving?

It’s funny because I think I’m guilty of some of what he’s criticizing.

I recently wrote that AI agents weren’t ready for prime time. I was drawing on Salesforce research around CRM-based agents that highlighted a number of weaknesses. I said the technology wasn’t ready yet, and a lot of people pushed back and told me I was wrong.

Chris Nichols, who continues to do amazing work at SouthState, had a more nuanced take. He basically said, “You’re right that they aren’t fully ready today, but the timeframe in which they will become ready is shrinking very quickly.”

I think the key is that there are different types of readiness.

There is technology maturity, and yes, that is improving faster than we’ve ever seen.

But there is also organizational readiness, process readiness, and industry readiness. You can’t simply throw away the existing organization and replace everything overnight. People don’t move that fast. Processes don’t change that fast. Systems are interconnected.

And if you ask any community-bank or credit-union executive, they’ll tell you, “That’s great, but I still have a core system weighing me down.”

So Karan is right about the speed at which the technology is becoming enterprise-ready. But technology readiness is not the same thing as organizational readiness.

What does amaze me is that some banks and credit unions are still taking a pure wait-and-see attitude. Even worse are the institutions that say, “We’re a fast follower.”

Being a fast follower actually requires you to be very good. A lot of institutions are deceiving themselves when they say that.

So yes, the technology curve is moving very quickly, but the organizational curve is moving more slowly.

I agree. I think the lesson is to be proactive rather than reactive.

During the pandemic, a lot of institutions were forced to digitally transform quickly. That’s when “digital transformation” became a buzzword in almost every vendor pitch.

Now we can see AI adoption happening in front of us. Instead of waiting until we’re forced to react, why not begin experimenting now?

Maybe you introduce a chatbot for six months or a year. Maybe you test one narrow workflow. Learn what works, learn what doesn’t, and build from there.

We keep coming back to the same idea: test, learn, and take marginal gains.

If anything, the quote is a reminder that institutions should not wait for the future to arrive before they start preparing for it.

So that’s AI. Now talk to me about the latest acquisition you wanted to bring up.

I wanted to talk about Xero, the cloud-accounting software company. It’s a very large global company, though not as dominant in the U.S. as it is in some other countries.

Xero acquired Melio, a relatively small company focused on small-business accounts payable, for roughly $2.5 billion.

I’ve spoken with the Melio team before and have always been impressed with what they were building.

The acquisition caught my eye because I think the small-business market is a huge opportunity for community banks and credit unions. That’s true not only from a lending perspective, but also from treasury management, payments, and broader operating services.

There is a lot of pain in the small-business market, and much of it is accounting-related.

A couple of years ago we did a study for a company that was then called Hurdlr and is now called Tight. They focus on embedded accounting through APIs.

The research showed that accounting functions consume an enormous amount of a small-business owner’s time. On average, I think it was close to 20 hours a week across bookkeeping, invoicing, expense tracking, financial reporting, and related tasks.

The second major finding was that small-business accounting technology is incredibly fragmented.

They might use QuickBooks or Xero for bookkeeping, one program for invoicing, another for expense tracking, another for financial reporting, and separate payment providers. Their financial operating systems are all over the place.

That’s why the Melio acquisition is so interesting. It gives Xero an opportunity to integrate payments directly into the accounting workflow.

Once that functionality is embedded, a Xero user can make payments and pay bills without leaving the accounting platform.

That is a significant benefit for small businesses. But it also represents another step toward embedded accounting and embedded payments, which can threaten the depth of a community financial institution’s relationship with small-business clients.

Banks want the lending relationship, but the operational relationship is often even stickier. If you can own accounts receivable, accounts payable, payments, and cash management, you become much more central to the business.

Look at the traction Autobooks has gotten. They’ve historically had more of an accounts-receivable focus, but they’re expanding into capital as well.

They launched a capital product recently, and Derek Sutton posted that within a short period they had funded about $1 million across roughly 90 small businesses.

I initially mixed up the numbers and said $90 million. Close enough. I had the 90 and the million in there somewhere.

But the larger point is that there is a major opportunity here.

This acquisition highlights how much value can be created by integrating accounting, payments, and lending for small businesses.

I think this is another example of what someone once said: the riches are in the niches.

It actually reminds me of when I worked at a supermarket in Brooklyn as a bookkeeper. We used physical general-ledger books, a No. 2 pencil, and handwritten debits and credits. If I made a mistake, I had to erase everything and redo it.

Now think about where we are today.

When I’m on the road talking with banks about growth, this kind of acquisition is a good example of how a bank can use fintech partnerships to build a more differentiated small-business offering.

Could a community bank white-label a capability like this? Could it make accounting and payments part of its small-business value proposition?

That could help the institution stand out from larger competitors.

Exactly.

I’ve got one more topic for today, something nobody has heard about in months or years: stablecoins.

Obviously I’m kidding. Stablecoins have received enormous attention in the last couple of weeks, especially with the passage of the GENIUS Act.

For people who haven’t dug into the details, the legislation does several important things. It creates regulatory clarity around stablecoins, establishes capital and liquidity standards, limits issuance to approved institutions, requires one-to-one backing with high-quality liquid assets such as U.S. Treasuries, and creates audit and reserve-disclosure requirements. It also limits algorithmic or unbacked stablecoins.

That kicked off a huge wave of commentary. Suddenly people were saying Walmart and Amazon would issue stablecoins, consumers would move all their money into them, and payments would migrate wholesale to stablecoins.

I think a lot of that is overblown.

The Bank for International Settlements recently published a paper arguing that stablecoins still fall short of functioning as a full replacement for money.

They used criteria such as singleness, meaning money should maintain equivalent value; elasticity, meaning the money supply should be able to respond to economic needs; and integrity, which includes security, privacy, and protection against illegal use.

Their conclusion was that stablecoins don’t fully meet those tests.

In the United States, we already have strong payment rails. I see a much clearer role for stablecoins in countries where those rails are weaker.

That said, I do think community financial institutions should pay attention.

If you serve businesses with significant international payment flows, stablecoins may have a useful role. If you serve consumers who frequently send money across borders, that’s another potential use case.

There may also be opportunities in commercial payments.

JPMorgan has already taken steps in this direction. It introduced its own blockchain-based payment mechanisms and now has tokenized deposit capabilities that function somewhat like stablecoins but are backed by bank deposits rather than Treasury reserves.

So I think the hype is ahead of the reality, but community banks should still understand what role stablecoins may eventually play in their strategy.

What do you think?

I have one simple thought: the Kardashian effect.

We’ve seen celebrities influence crypto. Now I wonder what happens when stablecoins become part of mainstream culture.

Is JPMorgan going to hire the Kardashians to promote tokenized deposits?

The broader point is that the government clearly recognizes that money is becoming increasingly digitized. I’m curious how other institutions imitate what the biggest players do and how quickly that behavior spreads.

You’re actually bringing up another topic that’s worth discussing.

You remember Tom Brady promoting crypto. I came across an academic research study this week from professors at several universities who analyzed thousands of social-media posts to measure the impact of celebrity crypto endorsements.

The findings were not particularly positive.

They found that people often lost money after acting on celebrity endorsements, and trading volume jumped sharply in the hour or two after celebrities posted about a token.

One thing that surprised me was which consumer segment appeared especially affected: older, educated, affluent men.

I saw that and thought, wait a second. This isn’t just a young-consumer problem.

Exactly. There’s no generational exemption from making bad financial decisions.

When you mention older affluent men being influenced by celebrity endorsements, it reminds me of the saying that the shoemaker’s children go barefoot.

People are busy. They may trust a celebrity for reasons that have little to do with financial expertise, and then that celebrity gives them a shortcut through an area that feels complicated.

That’s great for marketing. It isn’t necessarily great for the integrity of the information.

I think companies need to be increasingly intentional about who represents their brand and why.

If I’m looking for financial guidance, I’d rather listen to someone with actual experience in the field than a celebrity who happens to have reach.

It’s similar to using ChatGPT. If you ask a vague question, you may get a vague or misleading answer. You still have to understand enough to evaluate what you’re being told.

Brand integrity and information quality are becoming more important, not less.

By the way, I attached the academic paper to my LinkedIn post because I wanted to see whether posting the actual PDF would drive more engagement.

It did not. It was one of my worst posts of the month.

But Ron, look at you. You tested and learned.

Exactly. I’m living the Stacey Bryant philosophy: test and learn.

There we go.

Let’s wrap it up for this week.

Stacey, keep your eyes and ears open out there. You always have your ear to the ground, and I’m sure we’ll pick up some good topics for next time.

For everybody who enjoyed today’s episode, please hit the follow button on Spotify, Apple Podcasts, YouTube, or whatever platform you’re listening on. We’ve got more conversations coming, and we don’t want you to miss them.

Thanks for tuning in. We’ll see you next time.