Upstart turns to prime lending for partners like Alliant Credit Union

Upstart, an AI-based lending marketplace provider that traditionally served consumers who couldn’t get credit elsewhere, is shifting its attention to the types of prime borrowers that banks embrace. On Thursday, it’s launching a program called T-Prime that will allow banks and credit unions to target super prime borrowers using Upstart’s marketing channels and automated lending system.

For more than a decade, the San Mateo-based company has used artificial intelligence to analyze consumers with low or no credit scores, for example, recent college graduates with little credit history, and tried to identify “future prime” or “hidden prime” candidates. “. who are really good credit risks by looking at other data elements, including the types of jobs they have and their salaries.

As Upstart has established lending partnerships with more banks and credit unions, it has become clear that these financial institutions are more interested in providing prime loans to the most desirable borrowers.

An example of this is Alliant Credit Union, a digital-only credit union based in Chicago that serves employees of large companies and association members across the country. The credit union, which has no branches, has been working with Upstart for about a year, offering debt consolidation loans to consumers who have accumulated a lot of credit card debt.

“The goal that Upstart has now to serve some of these more important levels is a strong overlap with our interest in serving and acquiring new members,” said Dennis Devine, president and CEO of Alliant, in an interview. “We generate new members, we generate deposits, but we also want to be effective in providing high-quality loans to our members. That’s where a partner like Upstart can fit in. and grant credit, the partnership becomes very interesting for us.”

Upstart is now consciously targeting prime borrowers. The price ranges that the model can support have also been adjusted. It recently released a new algorithm, Model 18, which incorporates annual percentage lending rates.

“The APR is typically part of the output of a model: what APR should I charge this customer based on all these factors that we know?” said Upstart CEO Dave Girouard in a recent interview. “But the interesting thing is that the APR itself affects loan performance.”

If a customer is charged a higher APR, their monthly payment will increase and therefore their likelihood of default will also increase.

But there is also adverse selection at play: a person who is likely to accept a 15% loan typically has less creditworthiness than someone who is only willing to accept an 8% loan. By taking APR into account in credit decisions, Model 18 has boosted credit performance, Girouard said.

Devine declined to share how many loans the credit union has made through the Upstart platform.

“We started small,” he said. “We wanted to see if it would work. We wanted to see the member experience and how the credit would perform. They’ve been really good.”

The benefit of using an AI-based lending decision model rather than a more traditional FICO score-based underwriting system is that “the more data elements you have about an individual, you can make a much more thoughtful decision in relation to the risk that that individual may present the likelihood of repaying or not repaying,” Devine said. Upstart also adds economic forecast data that takes into account a borrower’s ability to repay, he said.

Alliant monitors model activity for risk, compliance and performance, he said.

According to Upstart, the main benefit that a platform provider like Upstart brings to banks and credit unions is a fully automated process.

“The process of originating an online loan, especially if you are a new customer who doesn’t already have a decades-long verification relationship with the bank, is often very difficult,” said Paul Gu, chief technology officer at Upstart, in a statement. interview. “It often involves going to a branch. It usually involves uploading documents. In our case, 90% of loans are verified instantly.”

And working with Upstart can help banks acquire new customers across the country, he said.

“This has been a problem we hear from banks and credit unions: how do I acquire net new customers in a digitally native way?” Gu said. “That’s not necessarily an easy thing. And it’s something we’ve spent the last 10 years refining the ability to do cost-effectively.”

Banks decide their pricing structure, in other words, the target APR, as well as the levels of risk they are willing to accept.

“Through the parameters they set, we have all the information we need from a purely mathematical standpoint to determine the APRs for any candidate,” Gu said.

Upstart itself is still interested in subprime borrowers, Gu said. But it is recognizing that core customers make up a large part of the addressable market.

Although AI-based lending has been around for more than a decade, it has yet to take off among major banks and credit unions.

A big factor in this hesitancy is regulatory uncertainty, according to Christine Livingston, managing director and global AI lead at Protiviti.

“The underwriting of credit risk decisions is subject to many specific regulations,” Livingston said in an interview. “Regulation is probably one of the main reasons why more organizations and banks haven’t used this type of platform.” Furthermore, for many banks it is difficult to change loan underwriting systems that are typically a component of a complex core system.

“You have to migrate legacy data, restructure and reorganize,” she said.

But there are also reasons to think that demand for AI-based lending will increase, she said.

“The best experience someone has anywhere becomes the minimum expectation of the experience they want anywhere,” she said. “I can go to Amazon and have literally everything I want delivered to my door, probably within 24 hours. And if I have a problem with it, I can easily fix it. I can return it. It’s an amazing experience.”

Consumers will start to expect this kind of ease from their banks, she said.

“The customer proposition of, oh, I don’t have to sit down and sign my life into a hundred different documents and wait a week to see if my loan gets approved, I definitely think there’s a really interesting consumer angle to that,” Livingston said. “I can see this being very attractive from a consumer perspective and for banks looking for efficiency in the underwriting process.”