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UPST

Upstart Holdings, Inc.

UPST

Upstart Holdings, Inc. NASDAQ
$44.94 6.85% (+2.88)

Market Cap $4.37 B
52w High $96.43
52w Low $31.40
Dividend Yield 0%
P/E 172.85
Volume 3.74M
Outstanding Shares 97.29M

Income Statement

Period Revenue Operating Expense Net Income Net Profit Margin Earnings Per Share EBITDA
Q3-2025 $285.899M $212.443M $31.805M 11.125% $0.329 $38.591M
Q2-2025 $257.291M $246.906M $5.607M 2.179% $0.059 $11.499M
Q1-2025 $220.391M $215.789M $-2.447M -1.11% $-0.026 $3.982M
Q4-2024 $226.395M $213.914M $-2.755M -1.217% $-0.03 $2.055M
Q3-2024 $172.958M $168.853M $-6.758M -3.907% $-0.075 $-1.323M

Balance Statement

Period Cash & Short-term Total Assets Total Liabilities Total Equity
Q3-2025 $836.905M $2.905B $2.161B $743.718M
Q2-2025 $400.556M $2.478B $1.756B $722.01M
Q1-2025 $605.365M $2.296B $1.62B $676.642M
Q4-2024 $793.607M $2.367B $1.734B $633.218M
Q3-2024 $450.224M $1.809B $1.213B $595.536M

Cash Flow Statement

Period Net Income Cash From Operations Cash From Investing Cash From Financing Net Change Free Cash Flow
Q3-2025 $31.805M $-122.629M $-120.506M $378.58M $135.445M $-122.704M
Q2-2025 $5.607M $-120.162M $-109.834M $91.928M $-138.068M $-120.277M
Q1-2025 $-2.447M $-13.486M $-78.569M $-44.68M $-136.735M $-19.645M
Q4-2024 $-2.755M $-110.926M $-77.909M $509.331M $320.496M $-110.926M
Q3-2024 $-6.758M $179.34M $-46.17M $-38.021M $95.149M $179.224M

Revenue by Products

Product Q3-2024Q4-2024Q1-2025Q2-2025
Borrower Fees
Borrower Fees
$10.00M $10.00M $10.00M $10.00M
Collection Agency Fees
Collection Agency Fees
$0 $10.00M $0 $0
Other Fees
Other Fees
$0 $0 $0 $0
Servicing Fees
Servicing Fees
$20.00M $40.00M $20.00M $20.00M
Servicing Fees Net
Servicing Fees Net
$30.00M $70.00M $30.00M $40.00M

Five-Year Company Overview

Income Statement

Income Statement Upstart’s revenue ramped up very quickly through 2021, then dropped off during the tougher lending environment and has only partially recovered since. The business moved from being nicely profitable in 2020–2021 to meaningful losses over the last three years, as operating costs stayed high while loan volumes fell. Margins are currently negative, but not disastrously so, suggesting a business that can swing between profit and loss depending on credit conditions and funding availability. The key question is whether management can grow volumes again while keeping expenses disciplined enough to restore consistent profitability, not just occasional profitable quarters.


Balance Sheet

Balance Sheet The balance sheet has grown substantially as the company scaled, with total assets rising and a notable build‑up of cash compared with its early years. Debt has also increased a lot and now sits well above the company’s equity base, which means leverage is a real point to watch, even if some of that debt is tied to funding loans rather than day‑to‑day operations. Equity has inched up only slowly, reflecting limited retained earnings because of recent losses. Overall, Upstart has a reasonably solid liquidity cushion, but its capital structure is more debt‑heavy than before, which adds sensitivity to credit markets and funding conditions.


Cash Flow

Cash Flow Cash generation has been very up and down. Upstart showed healthy operating and free cash flow in the high‑growth years, then swung to sizeable cash burn when the lending market tightened and volumes fell. More recently, cash flow has moved back into positive territory, which is encouraging and suggests the core model can generate cash when conditions are more favorable and costs are contained. Capital spending is very light, so most cash movement comes from working capital, loan funding dynamics, and operating performance rather than big investments in physical assets. The big uncertainty is whether positive cash flow can be sustained across a full credit cycle.


Competitive Edge

Competitive Edge Upstart sits at the intersection of finance and technology, trying to replace traditional credit scoring with AI‑driven underwriting. Its edge comes from using a very wide range of data points and continuously training models on growing amounts of repayment history, which can create a self‑reinforcing data advantage over time. The company operates as a technology partner rather than a bank, relying on a network of banks and credit unions to fund loans, which lets it scale without taking on the full weight of credit risk—but also makes it dependent on those partners’ confidence and on broader funding conditions. Competition is intense from both traditional lenders and other fintechs working on similar AI‑based models, and regulators are watching AI lending closely, so maintaining trust, compliance, and clear evidence that its models are fair and effective is essential to its long‑term position.


Innovation and R&D

Innovation and R&D Innovation is the heart of Upstart’s strategy. The company constantly refreshes its AI models, claims meaningfully better risk prediction than older credit methods, and has driven very high automation in loan approvals. This gives it a chance to offer faster decisions, potentially lower losses, and broader access to credit for borrowers who might be overlooked by traditional scores. Upstart is also widening its product set beyond personal loans into areas like auto loans and home‑equity products, aiming to become a broad, always‑on credit platform. The opportunity is substantial, but the company must keep proving that each new model and product works well through different economic conditions, and that its AI remains explainable, fair, and compliant with evolving regulations.


Summary

Upstart is an ambitious, AI‑driven lending platform that has already shown it can scale quickly and operate profitably in good times, but its results have been volatile and highly sensitive to credit cycles and funding conditions. Revenue and profits surged early after the IPO, then dropped as the lending environment turned, pushing the company into several years of losses before signs of improvement more recently. The balance sheet is larger and more liquid than in its early days but also more leveraged, making funding markets and partner confidence especially important. The core technology and data‑driven approach appear differentiated and are steadily expanding into new loan types, which could broaden the addressable market if execution is strong. Overall, this is a high‑innovation, high‑uncertainty story: success depends on proving that its AI models can consistently manage credit risk, navigate regulation, and deliver stable profitability across full economic cycles.