How Upstart Solves the Community Banking Crisis

Banks need help. Especially small and medium sized banks and credit unions.

Don’t believe me? Take a look at this chart.

Nearly half the community banks in the United States are gone.

What is happening to them and their customers?

They are being acquired by larger banks and financial institutions.

The reasons small and medium sized financial institutions are going the way of the dodo is revealed in this data from FRED (shared earlier on my X account).

It’s clear that in 2010, something changed. From the 90s until 2010, both small banks and large banks had somewhat similar delinquency rates on unsecured lending products, namely credit cards. These are products not secured by assets which banks can seize for enforcement of repayments.

So what happened, and why does this mean Upstart is a critical component to save small and medium sized financial institutions?

That sharp divergence you see starting around 2010 on the chart wasn't an accident. It was the direct, if unintended, consequence of the Dodd-Frank Act. Passed in the wake of the financial crisis, it was designed to stop the "Too Big to Fail" problem at giant Wall Street firms.

But in reality, it created a permanent structural disadvantage for smaller banks.

Here's how:

A Mountain of Rules: Dodd-Frank unleashed an avalanche of new regulations, nearly doubling the rulebook for banks. For a giant like JP Morgan, with an army of lawyers, this is just a cost of doing business.

A 2015 survey co-sponsored by the Federal Reserve System and the Conference of State Bank Supervisors (CSBS) estimated the annual compliance cost for community banks at $4.5 billion, a figure that represented a remarkable 22 percent of their collective net income in 2014.

The Analytics Arms Race: More importantly, the law forced big banks to build incredibly sophisticated, data-driven systems to stress-test their loan books. This regulation, meant to be a leash, accidentally became a catalyst for their tech capabilities. While large banks were forced to invest billions in data science to predict risk, smaller banks were spending their limited funds just trying to keep up with the paperwork. This created a permanent "analytics gap."

The very regulations meant to rein in Wall Street ended up giving them a massive, permanent technological edge, leaving smaller players in the dust.

A Rigged Game: Two Business Models, One Market

This tech gap led to two completely different ways of doing business.

Large Banks: The Top 10 issuers control 83% of the credit card market. They operate a high-volume, technology-driven model. Their goal isn't to give you a low interest rate. Their goal is to fund massive, multi-billion-dollar rewards programs (think airline miles and cash back) to attract high-spending customers.

If we look at the spread between Credit Card APR over the Prime lending rate, we see that after 2010, when Dodd-Frank went into effect, large banks have crept up interest rates beyond the cost of risk and borrowing.

Why are banks charging so much more post Dodd-Frank in interest on credit cards vs risk?

The CFPB found that large issuers charge interest rates that are 8 to 10 percentage points higher than smaller banks. It's not because their customers are riskier, it's because their business model requires high APRs to fund the marketing machine.

Now, let’s look at small banks.

Small Banks: Small banks can't compete in the rewards game. They don't have the scale to negotiate deals with airlines or fund national advertising campaigns. So what's left? How can they attract customers?

They are forced to compete on the only two things they have left: a lower interest rate and access. Meaning, a greater willingness to take on risk.

Which brings us back to this chart again.

They are strategically funneled into approving the very customers the big banks, with their superior data analytics, have chosen to pass over. They are competing on risk because the structure of the market leaves them no other choice.

This brings us to the problem that Upstart can solve.

The Upstart Value Thesis to Small & Medium Banks

Small banks are trapped. They need to offer credit cards to keep their customers, but they are getting crushed by higher delinquencies because they lack the analytical tools to price risk accurately.

This is where the value chain unbundling becomes their salvation. You have customer aggregators and you have underwriters. Which I wrote about here earlier this month.

Small banks and credit unions are customer aggregators. They have deep community roots, trust, and local relationships. That is their core strength.

What they lack is world-class, AI-native underwriting.

Upstart provides that underwriting. It is a pure-play, hyper-specialized underwriter. Its entire reason for being is to use artificial intelligence and massive datasets to generate a more accurate assessment of risk than traditional models. It has devoted hundreds of the world's best machine learning experts to solving this one complex problem.

By partnering with Upstart, a small bank doesn't have to build its own billion-dollar analytics division to compete. They can plug into one.

This allows the community bank to do what it does best. Serve its local customers, while relying on a best-in-class partner to handle the hyper-complex task of modern risk analysis.

It allows them to approve more customers at lower loss rates, improving profitability and breaking free from the trap of competing solely on risk.

The dramatic gap in that FRED chart isn't just a statistic. It shows a fundamental sickness in the competitive landscape of American banking.

For smaller institutions to survive and thrive, they must stop trying to be mediocre versions of the megabanks and instead embrace a new model of specialization.

Partnering with technology leaders like Upstart to close the analytics gap isn't just an option; it's an essential strategy for survival.

Disclosure: I am currently long Upstart. My full portfolio and allocation is available on SavvyTrader.

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