Upstart Stock tumbles 94% as end of stimulus pulls rug under fintech lender

Personal lender
is feeling the pressure as the rate of missed payments on its loans rises sharply after stimulus packages end. The Silicon Valley company specializes in personal loans that finance expenses such as credit card debt consolidation, weddings and home repairs. Upstart announces that its artificial intelligence-powered underwriting expands access to credit by examining more than a borrower’s FICO score, and it received praise from the Consumer Financial Protection Bureau for doing so. But with inflation and interest rates soaring, this is the first time Upstart’s model has been tested during a real economic downturn.

During the Covid-19 pandemic, low interest rates allowed fintechs like Upstart to lend money to consumers at competitive rates with little risk of default as borrowers collected stimulus checks. Today, rising interest rates and the end of government support programs are reducing Upstart’s results. Stimulus programs slowed to a halt in September after improved unemployment benefits ended. The delinquency rate, the percentage of loans that are in arrears, on Upstart loans originated in 2021 is approaching 7%, compared to less than 3% for loans originated the previous year, data from credit rating agency KBRA shows. Upstart’s stock has fallen 94% since its peak in October 2021, while the the broader publicly traded fintech market is down 55%. Upstart declined to comment due to the “quiet period” ahead of its next financial results report.

While analysts say rising delinquency rates are a normalization after stimulus payments reduced the risk of late payments, some were struck by the scale of the correction. “I don’t think we’re at the point yet where default rates or delinquency rates are above pre-COVID levels, but with this rollback, it’s not so much the levels as the rate of change, it’s which was surprising,” said Citi analyst Peter Christiansen.

Upstart acts as an intermediary between banking partners and borrowers, making money by bundling loans and selling them to third-party investors for a fee. Junior CFO
Sanjay Datta said on the company’s first-quarter earnings call that in some cases default rates had risen above pre-pandemic levels. Rising delinquency rates, a leading indicator of defaults, have shaken investor confidence in Upstart loans, making it harder for the company to find investors, analysts said.

In 2021, this forced Upstart to retain the loans, surprising shareholders. In the first quarter of 2022, Upstart held $598 million in loans on its balance sheetcompared to $252 million in the fourth quarter of 2021. Earlier this month, Upstart said in a Press release that its lending market was “funding constrained, driven largely by macro-economic concerns among lenders and capital market participants”.

For the second quarter, Upstart revenue was $228 million, $77 million lower than the company had previously expected, with an estimated net loss of around $30 million. Part of the drop in second-quarter revenue stemmed from Upstart selling the loans it held on its balance sheet to other lenders, in some cases at a loss, rather than its usual practice of bundling them into backed securities. to assets. In addition to these sales, Upstart experienced a decline in loan volume in the second quarter, which reduced its revenue.

The reduced volume could be the result of higher interest rates and tighter lending standards from Upstart or its partner banks. In a set of loans sold to investors from 2022, 30% of borrowers had FICO scores below 619 (scores range from 300 to 850, with the average American being around 715). Between 2017 and 2021, Upstart focused on providing loans to borrowers with lower FICO scores. However, as losses increase with higher delinquency rates, Upstart appears to be tightening its lending standards to reduce losses. In a more recent round of lending from 2022, only 24% of borrowers had FICO scores below 619. Ultimately, Upstart can only lend within the risk tolerance of its partner banks.

“Whatever model of AI you have, you’re ultimately at the mercy of the capital you can deploy at any given time and the risk tolerance behind that capital,” Christiansen said.

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