“Our record quarter reflects a flywheel that is clearly working: partners are sending more volume, adopting more products, and our network effects compound with every relationship we add,” said Gal Krubiner, CEO and co-founder, on Thursday’s (July 30) investor earnings call.
Network volume rose 33% year over year to a record $3.5 billion, beating Pagaya’s outlook. Total revenue and other income increased 19% to $387 million, while adjusted EBITDA climbed 43% to roughly $124 million. GAAP net income attributable to shareholders reached $45 million, up from about $17 million a year earlier.
At the same time, fee revenue less production costs as a share of network volume fell to 4.2% from 4.8%. Pagaya attributed the compression to asset mix, newer partners and products, and tighter pricing on asset-backed securities amid elevated capital costs.
Executives stressed to investors on the call that Pagaya’s AI advantage is becoming less about underwriting alone and more about orchestration: embedding inside lender workflows, expanding distribution and matching loan supply with institutional capital at scale.
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Pagaya’s AI Lending Flywheel Is Growing Faster Even as Its Take Rate Shrinks
CEO and Co-Founder Krubiner said the company’s flywheel is accelerating as existing partners send more volume, adopt more products and increase the value of Pagaya’s network with each added relationship.
The model differs from conventional lending growth. Pagaya does not need to acquire every borrower directly or finance every loan with its own balance sheet. It grows when banks and other lenders route more applications through its infrastructure and use the platform across a wider portion of their credit operations.
Pagaya completed six asset-backed securitizations totaling a record $3.7 billion during the quarter. The final three deals were upsized, and the company added another Auto forward-flow agreement.
Company leadership said Pagaya is advancing further up its partners’ lending funnels, helping them operate as “full spectrum lenders.” Annualized Auto network volume reached a record $4.8 billion during the quarter.
The company may be more asset-light than a traditional lender, but it remains exposed to credit performance, funding costs and securitization demand.
See more: Pagaya Issues $300 Million in Bonds to Fund BNPL Loans
Auto Industry Is Becoming Pagaya’s Distribution Engine
Auto drove much of the company’s network-volume growth. During the earnings presentation, management said Pagaya’s connected dealership network now reaches roughly 40% of the U.S. auto market. It also highlighted greater use of “first-look” and “dual-look” channels, allowing its models to assess borrowers earlier in the financing process.
That expands the addressable market while reducing dependence on declined-loan traffic.
For dealers, broader approval capacity can help convert more shoppers into buyers. For lenders, Pagaya can increase coverage without forcing a wholesale replacement of internal underwriting systems. For Pagaya, each integration creates more application flow and more opportunities to introduce additional products.
The advantage is therefore not simply a better credit model. Predictive tools are increasingly available across the industry. The more defensible asset is the network connecting lenders, dealerships and institutional investors.
The most persuasive evidence for Pagaya’s model appeared in its cost structure. Adjusted EBITDA margin expanded to 32% from 26%. Core operating expenses declined to 31% of fee revenue less production costs, compared with 39% a year earlier. That is the financial test facing many AI platforms. Models can improve productivity, but durable value emerges only when incremental activity grows faster than the expense base supporting it.
Pagaya increased its full-year GAAP net income outlook to between $155 million and $180 million. It also expects network volume of $12.5 billion to $13.25 billion and adjusted EBITDA of $460 million to $490 million. The next test is whether the company can sustain that equation through less favorable credit and capital-market conditions.
