UPST Stock: Insider Activity, Filings & Research
Upstart Holdings, Inc. (UPST) — Drillr’s hub for UPST insider activity, SEC filings, earnings signals and AI research. Over the trailing 3 months, UPST insiders filed 3 open-market buys and 11 sales (SEC Form 4).
UPST insider trading activity (SEC Form 4)
| Date | Insider | Type | Shares | Price |
|---|---|---|---|---|
| Jun 2, 2026 | O'Kelly Ciarandirector | Grant | 6,476 | — |
| Jun 2, 2026 | Hentges Marydirector | Grant | 6,476 | — |
| Jun 2, 2026 | Terry Hilliard C. IIIdirector | Grant | 6,476 | — |
| Jun 2, 2026 | Wennes Timothy Hdirector | Grant | 6,476 | — |
| Jun 2, 2026 | Cooper Kerry Whortondirector | Grant | 6,476 | — |
| Jun 2, 2026 | Bernard Peter Jdirector | Grant | 6,476 | — |
| May 27, 2026 | Mirgorodskaya Nataliaofficer: See Remarks | Sell | 974 | $28.99 |
| May 22, 2026 | Darling Scottofficer: Chief Legal Officer | Sell | 6,634 | $28.78 |
| May 22, 2026 | Datta Sanjayofficer: President, Capital& Enterprise | Sell | 7,985 | $28.77 |
| May 22, 2026 | Mirgorodskaya Nataliaofficer: See Remarks | Sell | 526 | $28.77 |
| May 18, 2026 | Blankmeyer Andreaofficer: Chief Financial Officer | Sell | 101 | $30.54 |
| May 18, 2026 | Darling Scottofficer: Chief Legal Officer | Sell | 286 | $28.84 |
| May 18, 2026 | Blankmeyer Andreaofficer: Chief Financial Officer | Sell | 2,759 | $28.96 |
| May 18, 2026 | Mirgorodskaya Nataliaofficer: See Remarks | Option | 4,600 | $1.35 |
| May 18, 2026 | Darling Scottofficer: Chief Legal Officer | Sell | 441 | $29.99 |
Source: UPST SEC Form 4 filings, latest Jun 2, 2026. For informational purposes only — not investment advice.
Upstart Holdings, Inc. company profile
Overview
Upstart Holdings, Inc. (NASDAQ:UPST) is a financial technology company founded in 2012 and headquartered in San Mateo, California. The company went public in December 2020 and operates an artificial intelligence-powered lending platform that connects borrowers with institutional lenders. Upstart has evolved from focusing solely on personal loans to expanding into multiple lending verticals including auto loans, home equity lines of credit, and small-dollar lending. The company positions itself as a technology innovator in the traditional credit underwriting space, using machine learning models to assess creditworthiness beyond conventional credit scores.
Business
Upstart operates a cloud-based artificial intelligence lending platform that serves as an intermediary between borrowers seeking loans and institutional lenders providing capital. The platform uses sophisticated machine learning algorithms to underwrite loans, moving beyond traditional FICO credit scores to incorporate thousands of data points for more accurate risk assessment. The company's core offering is personal loans, which represents the largest portion of its business. These are typically unsecured loans ranging from $1,000 to $50,000 that consumers use for debt consolidation, major purchases, or life events like weddings. The personal loan segment generates approximately 70-80% of total origination volume. Auto lending represents the second major vertical, focusing primarily on auto refinancing rather than purchase financing. This segment has shown rapid growth, with originations increasing nearly 5x year-over-year in recent quarters, though it still represents a smaller portion of total volume. The Home Equity Line of Credit (HELOC) product allows homeowners to borrow against their home equity. Launched relatively recently, this product is now available in 37 states and has demonstrated strong sequential growth, with originations growing over 6x year-over-year. Small-dollar lending targets borrowers seeking smaller loan amounts, typically under $5,000. This segment represents approximately 15% of loan count but only 3% of total dollar originations due to the smaller average loan size. The platform processes loan applications through an automated system that can approve over 90% of loans instantly without human intervention. This automation reduces processing costs and provides borrowers with immediate decisions, differentiating Upstart from traditional lenders that may take days or weeks to process applications.
Revenue model
Upstart generates revenue primarily through fee-based income rather than interest income, positioning itself as a technology platform rather than a traditional lender. The company earns fees from its bank and institutional lending partners for each loan originated through its platform. These fees typically range from 3-8% of the loan amount, depending on the loan type, risk profile, and market conditions. The company's customers are institutional lenders including banks, credit unions, and alternative investment funds who pay Upstart for access to pre-underwritten loan opportunities. These partners value Upstart's AI-driven risk assessment and the platform's ability to deliver consistent loan flow with predictable risk characteristics. Upstart also generates servicing revenue by managing loan payments and customer relationships on behalf of lending partners. Additionally, the company occasionally holds loans on its balance sheet, earning net interest income, though this represents a smaller and more variable portion of total revenue. Several factors influence Upstart's margins and profitability. Interest rate environments significantly impact demand, as higher rates reduce borrower appetite and tighten lending partner criteria. Economic conditions affect both loan performance and funding availability, with economic uncertainty typically leading to more conservative underwriting and reduced loan volumes. Competition from traditional banks, fintech lenders, and other AI-driven platforms can pressure take rates and require increased marketing spend. Regulatory changes in consumer lending or data privacy could impact the company's underwriting models or operational costs. Model accuracy improvements can expand addressable markets and improve conversion rates, while funding partner relationships and committed capital arrangements provide stability during volatile periods.
Competitive moat
Upstart's primary moat centers on its proprietary AI models and data advantage accumulated over more than a decade of lending operations. The company has processed millions of loan applications and observed their performance outcomes, creating a substantial dataset that becomes more valuable over time. This data flywheel effect means that as Upstart originates more loans, its models become more accurate, which attracts more lending partners and borrowers, generating additional data. The company's automation capabilities provide operational advantages, with over 90% of loans processed without human intervention. This creates cost advantages and faster processing times that are difficult for traditional lenders to match without significant technology investments. However, Upstart's moat faces several challenges. Large technology companies like Amazon, Google, or Apple possess greater resources and could potentially enter the lending space with competitive AI capabilities. Traditional banks are increasingly investing in their own AI and machine learning capabilities, potentially reducing their dependence on third-party platforms. Regulatory risks around algorithmic lending and fair lending practices could limit Upstart's model advantages. The company's network effects are relatively modest compared to true platform businesses, as lending partners and borrowers don't directly interact with each other. The switching costs for lending partners are also limited, as they can work with multiple platforms simultaneously. Overall, Upstart maintains a moderate moat based on its data and technology advantages, but this moat is not insurmountable and faces ongoing competitive and regulatory pressures. The company's long-term success depends on continuously improving its models faster than competitors and maintaining strong relationships with funding partners.
Risks & safety
Upstart demonstrates a reasonable margin of safety from a liquidity perspective but faces profitability and valuation challenges. • Cash position: Strong with $605 million in cash and short-term investments as of Q1 2025, providing substantial runway • Current ratio: Healthy at 4.06x, indicating good short-term liquidity • Debt levels: Debt-to-equity ratio of 2.04x is elevated, though much of this represents loan funding obligations rather than traditional corporate debt • Cash flow: Recently turned positive on operating cash flow in 2024 ($186 million) after negative flows in prior years, though free cash flow remains volatile • Profitability: Company is approaching GAAP profitability with small losses in recent quarters and positive adjusted EBITDA • Valuation concerns: Trading at high multiples with P/E ratios not meaningful due to minimal earnings, and EV/EBITDA ratios extremely elevated when EBITDA is low • Revenue volatility: Business model creates inherent revenue volatility based on funding availability and economic conditions • Balance sheet risk: Company occasionally holds loans on balance sheet, creating credit risk exposure during economic downturns
Recent development
Over the past few years, Upstart has undergone significant strategic evolution and operational improvements. The company has dramatically enhanced its AI model capabilities, with recent launches of Model 18 and Model 19 incorporating advanced techniques like embeddings and Payment Transition Models. Management reports that 18% of all accuracy gains since the company's inception occurred in just the last 12 months, demonstrating accelerating innovation. Product diversification has been a major strategic pivot, expanding beyond personal loans into auto lending, home equity lines of credit, and small-dollar lending. The HELOC product has grown from 11 states to 37 states and shows strong adoption with over 6x year-over-year growth. Auto lending has similarly expanded with nearly 5x year-over-year growth, while small-dollar lending has nearly tripled year-over-year. The company has fundamentally restructured its funding strategy, moving from primarily spot-market funding to over 50% committed capital partnerships. Major partnerships include arrangements with Fortress Investment Group, Blue Owl, and other institutional investors, providing more stable funding across economic cycles. This shift addresses one of the company's historical vulnerabilities around funding availability during market stress. Operational efficiency improvements include achieving over 90% loan automation rates, reducing model inference latency, and implementing the T-Prime program to target super-prime borrowers with competitive rates. The company has also significantly reduced its workforce and operating expenses while maintaining technology investment levels. Recent strategic partnerships include integration with Walmart's OnePay platform and expansion of the certified digital retailing network for auto loans. The company has added dozens of new lending partners and continues to invest heavily in AI infrastructure and model development capabilities.
UPST company profile · for informational purposes only — not investment advice.
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