September 11, 2024

VIA EDGAR SUBMISSION

Securities and Exchange Commission

Division of Corporation Finance

Office of Technology

100 F Street, N.E.

Washington, D.C. 20549

Ladies and Gentlemen:

On behalf of Upstart Holdings, Inc. (the “Company”), we are responding to the comments of the staff (the “Staff”) of the Securities and Exchange Commission (the “Commission”) contained in its letter dated August 13, 2024, to Sanjay Datta, the Company’s Chief Financial Officer, regarding the above referenced Form 10-K (the “Form 10-K”) filed on February 15, 2024 (File No. 001-39797).

In this letter, we have recited the comments from the Staff in bold and italicized type and have followed each comment with the Company’s response. References to “we,” “our” or “us” mean the Company or its advisors, as the context may require.

Annual Report on Form 10-K for the Fiscal Year Ended December 31, 2023

Our AI Lending Models, page 8

1. We note your disclosure that your AI models have increased in terms of the number of variables, the number of total data points. We also note your discussion on page 90 that discusses the variable performances of different vintages of loans compared to the targeted performance rate. Please tell us, with a view towards revised disclosure, the factors that led lower than forecast performance for recent vintages, despite the access to additional data. Similarly, please tell us how you determined that loans originated in 2023, which would have the least seasoning, are expected to revert to target level performance.

Securities and Exchange Commission

September 11, 2024

Page 2 of 3

We consider credit performance of Upstart-powered loans to be one of the most important measures of the effectiveness of our AI models. However, credit performance is impacted by multiple factors, including those our models do not predict, such as macroeconomic conditions. We have stated that we currently forecast vintages of core personal loans that originated in the first quarter 2021 through the third quarter 2023 to underperform relative to their target returns. Even though our underwriting models have over time utilized more variables and data points about borrowers which has improved model performance, they did not predict the severe impact of recent changes to macroeconomic conditions, credit market volatility and interest rate fluctuations, all of which were (and still are) beyond our control. The forecasted underperformance reflects the impact of a combination of factors that occurred during that period, including the elimination of government stimulus measures and the worsening of the macroeconomic environment, such as rising inflation and the resulting sharply higher interest rates. The macroeconomic conditions during that period led to more borrowers not making payments on their personal loans than anticipated by our models. For example, borrowers likely prioritized repayment of loans that are secured by necessities, such as mortgages or auto loans, over unsecured personal loans. Higher interest rates also likely led to higher payment obligations, which reduced the ability of borrowers to remain current on their obligations. These factors led to increased delinquencies, defaults and bankruptcies declared by borrowers, resulting in more charge-offs and fewer recoveries, all of which had an adverse effect on the credit performance of loans facilitated on our marketplace during that time period. To respond to macroeconomic changes more rapidly, we introduced the Upstart Macro Index (“UMI”) in 2023, which estimates the impact that observed macroeconomic changes may have on credit performance for Upstart-powered unsecured personal loans. The Company respectfully advises the Staff that it will revise its disclosure accordingly to address the Staff’s comment.

We stated that the core personal loans that originated in the fourth quarter of 2023 or later are currently forecasted to deliver returns in line with target yields. This reversion in credit performance expectations reflects a combination of factors, including increased conservatism in underwriting. Our most recent AI models benefited from more data on borrower repayment patterns in the period of significant macroeconomic changes and resulted in substantive positive changes in observed and expected borrower repayments even for vintages with limited seasoning. This makes our more recent models more accurate than those used in early 2021. Also, the relative stabilization of macroeconomic conditions, as reflected in UMI, has helped credit perform in line with our model’s predictions as there has been less unexpected volatility in macroeconomic factors impacting loan performance. The Company respectfully advises the Staff that it will enhance its disclosure accordingly to address the Staff’s comment.

Securities and Exchange Commission

September 11, 2024

Page 3 of 3

Our Ecosystem

Value Proposition to Lending Partners and Institutional Investors, page 11

2. We note that you permit your lending and institutional partners to control their programs when originating loans through your platform. Please tell us, with a view towards enhanced disclosure, the extent to which your lending partners rely on your credit scoring model alone, rather than in conjunction with traditional income and credit scores to approve loans.

Our lending partners continue to control their programs when originating loans through our platform, so do not solely rely on our models alone. Each lending partner sets and approves its own underwriting policy that establishes certain credit underwriting requirements determined by the lending partner. These “hard” requirements or criteria may include, without limitation, minimum FICO score, minimum verifiable annual income, and maximum debt to income ratio. Upstart applies the lenders’ hard criteria prior to feeding any information to its underwriting models. The majority of credit denials on the platform are due to the lending partners’ hard criteria from their underwriting policies. Borrower applications that meet a lender’s hard credit criteria are then assessed by a pricing model which takes into account the output of the Upstart risk scoring model in addition to additional pricing requirements set by lenders, such as target return objectives and maximum allowable APR limits. This process allows our lending partners to leverage our technology within the scope of their existing underwriting policies. The Company respectfully advises the Staff that it will enhance its disclosure accordingly to address the Staff’s comment regarding our lending partners reliance on our models alone.

* * * * *

Please direct any questions or comments with respect to the Company’s responses to me at scott.darling@upstart.com. Thank you for your assistance.

Sanjay Datta, Upstart Holdings, Inc.

Christopher Ing, Upstart Holdings, Inc.

Allison B. Spinner, Wilson Sonsini Goodrich & Rosati, P.C.

Shannon R. Delahaye, Wilson Sonsini Goodrich & Rosati, P.C.