Pagaya Technologies (PGY): Investment Thesis Explained

Just before the 4th of July weekend, I asked you for stock ideas to dig into during the break.

Out of more than 200 suggestions — many of which I already knew — Pagaya Technologies (PGY) stood out.

It looked undervalued and misunderstood, weighed down by past issues but showing signs of a turnaround. It felt like the perfect candidate for a deeper dive.

Let’s get into it.

Origins

Pagaya Technologies was founded in 2016 in Israel by Gal Krubiner (CEO), Avital Pardo (CTO), and Yahav Yulzari (CBO) — three longtime friends and entrepreneurs who had already worked together on real estate and finance ventures prior to starting the company. Their friendship and shared entrepreneurial spirit laid the groundwork for what would later become one of Israel’s most notable fintech success stories.

The inspiration for Pagaya emerged not from a single idea, but from a deep, ongoing conversation between the three co-founders about the future of finance. As Gal Krubiner recalled in an interview, a pivotal phone call changed their trajectory: “Real estate is nice, finance is nice — but tech is where the magic is happening.” They realized that to truly build something impactful and scalable, they had to move beyond traditional asset classes and embrace the power of technology, particularly AI and data science.

Their entry point into tech-enabled finance began with peer-to-peer lending, which at the time was a nascent and loosely defined segment. As they studied it more closely, the opportunity became clear: consumer credit was a $4T market — and yet it was underserved by traditional financial institutions and largely ignored by institutional asset managers. The trio saw a massive gap between demand and access, particularly among consumers who were deemed “unscorable” by legacy credit systems.

The company’s name, Pagaya, is derived from the Hebrew word פגיעה (pagiah), meaning “impact” or “connection.” This reflects the firm’s mission: to bridge the disconnect between borrowers and lenders, data and decision-making, capital and opportunity.

Founding Philosophy: Data Over FICO

Pagaya’s core insight was that legacy credit scoring systems — especially the widely used FICO model — were not equipped to assess modern credit risk. FICO is static, backward-looking, and rule-based, relying on a limited set of historical variables. This leaves out entire segments of the population: immigrants, gig workers, young professionals, or anyone without a long credit history. These consumers may be creditworthy, but the system fails to recognize their potential.

Pagaya’s founders believed that machine learning and alternative data could unlock access to credit for these underserved individuals. Drawing from Avital Pardo’s experience as the first data scientist at Fundbox, the team built AI models capable of ingesting hundreds of variables per applicant — including bank transactions, income patterns, job history, and behavioral indicators — to assess creditworthiness in real time.

Rather than becoming a lender themselves, they envisioned Pagaya as a B2B2C infrastructure layer. The idea was to embed their AI models directly into the origination workflows of banks, credit unions, and fintech lenders. This would allow financial institutions to say “yes” more often while maintaining risk discipline — and without Pagaya needing a banking license or large balance sheet.

Early Days and Initial Capital

Pagaya launched its first major product in personal loans, initially under an asset management model that used AI to guide investment decisions. The company raised capital to manage on behalf of institutions and launched the Pagaya Opportunity Fund in 2018. Early investors believed the technology had the potential to one day manage sovereign-level capital.

However, as the founders would later acknowledge, the initial business model had limitations. The market for electronic, AI-driven asset management was not yet mature enough to support rapid scaling. By 2019, the team made a decisive pivot: rather than solely managing money, Pagaya would offer its AI infrastructure directly to U.S. lenders to improve underwriting decisions. That transition — from AI-driven asset management to an embedded lending platform — was a defining moment in the company’s journey.

Growth and Transition to the U.S.

From that inflection point, Pagaya rapidly expanded across the U.S. consumer credit market. The U.S. offered scale, regulatory fragmentation, and a deep ABS market — all favorable conditions for Pagaya’s model. The company soon began diversifying beyond personal loans into auto lending and point-of-sale (POS) financing. In 2024, it relocated its headquarters to New York City — a strategic move to strengthen relationships with institutional investors and reinforce its presence in the U.S. financial ecosystem.

Pagaya’s API-based integration allowed banks and fintechs to embed its AI underwriting tools seamlessly into their lending flows. The result was a frictionless experience for consumers — and a powerful tool for lenders to expand credit access responsibly.

One of Pagaya’s most important early milestones was partnering with U.S. Bank, one of the top five banks in the country. This institutional validation unlocked further growth and helped attract other top-tier financial partners.

SPAC Merger and Public Listing

In June 2022, Pagaya went public via a SPAC merger with EJF Acquisition Corp, in a deal that valued the company at $8.5B on a pro forma basis. The listing was one of the largest fintech SPAC transactions to date and provided Pagaya with significant capital to scale its AI platform, expand lending partnerships, and deepen its U.S. presence.

Shortly after going public, Pagaya became the subject of intense market speculation. In late July 2022, a dramatic short squeeze sent the stock surging by more than 1,000% in a matter of days, briefly making it one of the most talked-about SPAC stocks of the year. The float was extremely limited due to the high redemption rate by SPAC shareholders prior to the merger, which contributed to the sharp volatility and attracted retail trading interest.

However, the rally was short-lived. As the float gradually increased and liquidity returned, Pagaya's stock price collapsed almost as quickly as it had risen. The extreme volatility drew scrutiny and contributed to broader skepticism surrounding SPAC structures, especially in the fintech space.

Compounding this were difficult macroeconomic conditions. Rising interest rates, tightening liquidity, and a sharp slowdown in consumer lending activity weighed on Pagaya’s core business. The company faced several problems that created significant pressure on reported earnings and sentiment, further exacerbating the stock’s decline throughout 2022 and into 2023.

Despite these headwinds, Pagaya remained focused on strengthening its platform fundamentals. The company continued to expand its network of bank and fintech partners, and refined its AI-driven underwriting models. This strategic focus — coupled with a shift toward more capital-efficient structures — positioned the company to emerge from the downturn as a more resilient and scalable infrastructure provider.

“That experience matured us. Emotionally, it was a rollercoaster. For employees, it was the dream and its collapse, and all the noise made it hard to focus. But we came through it. There’s now a strong understanding and connection between the team and our business results. Ultimately, we’re helping people get access to credit, and that clarified our mission.”

Business Model

Executive Summary

Pagaya Technologies operates a distinct B2B2C fintech platform that leverages AI to underwrite consumer credit at scale. Unlike traditional lenders, Pagaya neither originates loans nor holds significant long-term exposure to them. Instead, its core business revolves around using proprietary AI models to assess credit applications, enable seamless loan origination through banking partners, and monetize the process via fee income tied to both underwriting and capital markets activities.

This model — asset-light, fee-driven, and data-centric — positions Pagaya as a "technology-first enabler" in the lending ecosystem. It combines AI-driven underwriting with capital markets structuring to serve a dual customer base: (1) lending institutions seeking better loan decisioning and (2) institutional investors looking for yield-generating consumer credit exposure.

Core Mechanics of Pagaya’s Business Model

1. B2B2C AI Lending Enablement

Pagaya operates at the intersection of lenders, borrowers, and investors. It embeds its AI underwriting technology within the platforms of over 30 financial institutions — including US Bank, SoFi, Ally Financial, and Klarna — to assess consumer loan applications.

• Partner Integration: Pagaya receives a second look at loan applications rejected by partner banks. This is enabled through real-time API connections that share applicant data for evaluation.

• White-Labeled Approach: Consumers remain unaware of Pagaya’s involvement, as the loan still appears to be issued by the partner institution.

• Credit Models: Custom-built per partner, Pagaya’s credit models analyze hundreds of variables (income, employment stability, spending behavior, etc.) beyond traditional FICO metrics to predict default probability.

The more data Pagaya collects across different loan types (personal, auto, POS), geographies, and institutions, the better its models perform — creating a flywheel effect and a durable data advantage.

While many companies claim to use AI, Pagaya emphasizes that AI alone isn’t enough — what truly differentiates their platform is the quality, breadth, and volume of data feeding into their models.

Pagaya processes nearly $1 trillion in loan applications per year across a wide range of asset classes and lender types, from traditional banks to fintechs. This gives them visibility across the full credit spectrum, enabling their models to be more accurate, inclusive, and resilient than those trained on narrower or more siloed datasets.

In short:

• AI is only as good as the data behind it — and Pagaya has one of the most comprehensive data sets in the lending industry.

• This scale gives Pagaya a durable competitive edge that's difficult for other tech-enabled lenders to replicate.

Pagaya, in turn, offers a powerful value proposition to lenders:

• Higher approval rates, without higher risk: Pagaya uses AI to assess creditworthiness more accurately, enabling lenders to approve more customers — including those they might otherwise decline — without taking on additional risk.

• No Balance Sheet exposure: Lenders don’t need to keep the loans on their books. Pagaya connects them to institutional investors who fund the loans, so lenders earn fees without using their own capital.

• Customer Retention: Because the loan originates from the lender's brand (e.g., a bank or fintech app), the customer relationship stays intact — even though the funding and underwriting come from Pagaya’s network.

• Frictionless Integration: Pagaya plugs into the lender’s existing flow, often behind the scenes. This allows lenders to expand credit access with minimal disruption to their current operations.

In short: Pagaya helps lenders say “yes” more often, keep their customers, earn fees — all while taking zero balance sheet risk.

That’s why no lender has EVER stopped using Pagaya’s services.

2. Loan Funding Through Capital Markets

Once a loan is approved via Pagaya’s algorithm, the funding does NOT come from the partner bank. Instead, it is provided by third-party capital sources. These include:

• Asset-Backed Securitizations (ABS): Pagaya originates and packages loans into securities, which it sells to institutional investors.

• Forward Flow Agreements: Pre-arranged agreements where large capital partners agree to purchase loans directly (BEFORE loans are originated).

• Pass-Through Structures: Allow institutions to gain exposure without securitization overhead.

Non-ABS funding channels like forward flows and pass-throughs are increasingly important, particularly due to their lower risk retention requirements.

3. Revenue Model

Pagaya earns fees at multiple points in the value chain:

• AI Integration Fees: Paid by partners when Pagaya’s technology facilitates loan origination.

• Capital Markets Execution Fees: Earned from structuring and selling ABS transactions.

• Contractual/Administrative Fees: Recurring fees for servicing and managing securitization vehicles.

• Performance Fees: Earned when ABS transactions outperform preset benchmarks.

• Interest Income: From retained risk portions (typically the bottom 3–5% of ABS structures), though this is a minor revenue stream.

The key performance metric is FRLPC (Fee Revenue Less Production Costs) as a % of network volume. As of Q1 2025, this margin hit a record 4.8%, up from ~2.5% in 2022. It captures the economic value the company earns per dollar of loan volume after deducting the direct costs of producing those loans.

This improvement in FRLPC is not only a sign of healthier unit economics but also reflects a structural shift in the composition of Pagaya’s fee streams. Back in Q2 2022, nearly all of Pagaya’s FRLPC came from investor-related products — namely capital markets execution and contract fees tied to ABS issuance. At the time, 99% of FRLPC was derived from this side of the business.

Since then, the revenue mix has evolved meaningfully. By Q1 2025, 77% of FRLPC came from lending partner products, particularly AI integration fees. This shift highlights Pagaya’s increasing reliance on its embedded partnerships with banks and fintechs, which generate more predictable, recurring, and higher-margin revenue. At the same time, it reduces the company’s exposure to capital markets volatility.

Essentially, this trend illustrates how Pagaya’s business model is becoming both more profitable and more resilient as it matures.

4. Capital Efficiency and Risk Retention

Pagaya’s business model is capital-light but not capital-free. Regulatory frameworks require it to retain a small equity slice (~3–5%) of every ABS deal (per Dodd-Frank). These are the riskiest tranches — subject to first loss in case of defaults.

However, the high FRLPC margin (now ~4.8%) exceeds the required risk retention (~4%). This means Pagaya’s fee income can theoretically offset 100% of retained credit losses — a structurally important point for future profitability.

This also marks a critical inflection point. In prior years (2022–2023), Pagaya absorbed hundreds of millions in impairments on retained tranches due to thin credit buffers and high cost of capital. In contrast, its 2025 model is structured to be self-funding and resilient to modest defaults.

5. Scalability Through Operating Leverage

Pagaya benefits from substantial operating leverage. Core OpEx (G&A, R&D, Sales) has fallen even as revenue and network volume have grown. In Q1 2025, operating expenses were down 27% YoY, while revenue grew 19%.

Because infrastructure, data ingestion pipelines, and AI models are already in place, network volume can scale significantly without linear increases in cost. The company estimates it could double network volume without meaningfully increasing OpEx — a key driver of margin expansion.

6. Expansion Channels and Strategic Growth Levers

• New Partner Onboarding: Pagaya has grown from 20 partners to 31 in two years and is targeting 40–50 by 2026. Every new partner brings a ramp in origination volume and unique training data for AI models.

“We are in discussions with 80% of the top 25 banks in the U.S.”

• New Loan Products: Having expanded from personal loans to auto and point-of-sale loans (POS), Pagaya is also launching “Prescreen” and “Marketing Acquisition Engine” products to help partners reach more borrowers proactively.

• Theorem Acquisition: Last year, the company acquired an alternative asset manager with ~$3B AUM, providing a new captive source of capital and distribution for Pagaya loans.

• BNPL Opportunity: A critical growth area. Pagaya now underwrites Klarna’s installment loans for Walmart’s OnePay, replacing Affirm.

All in all, Pagaya has built a differentiated, scalable, and capital-efficient model to serve the next generation of consumer credit. By combining AI decisioning with capital markets execution, the company monetizes the full underwriting-to-funding lifecycle while avoiding the credit risk burden of a traditional lender.

The model’s strength lies in its modular architecture: it can add new partners, loan types, and funding channels without bloating its balance sheet or workforce. With high FRLPC margins and operating leverage kicking in, the path to sustainable GAAP profitability in 2025 looks increasingly credible (already achieved in Q1, ahead of expectations) — provided credit quality remains stable and capital flows continue.

Pagaya vs. Upstart: Two Diverging Models for AI-Driven Credit

Pagaya and Upstart are both using AI to modernize consumer credit, but their business models, risk profiles, and strategic roles in the lending ecosystem are structurally different.

Pagaya functions as a B2B2C infrastructure provider. It doesn’t originate loans, operate a consumer-facing platform, or allow banks to use its AI models independently. Instead, it embeds its underwriting engine directly into its partners’ front-end systems. That means consumers apply for loans through their existing bank or lender — not Pagaya — and Pagaya handles everything behind the scenes, from credit decisioning to capital markets execution.

Importantly, Pagaya is also responsible for securing the capital behind those loans. It funds originations primarily through ABS and other private credit structures. In fact, Pagaya is now the largest ABS issuer in the personal loan market and retains only a small “first-loss” slice in each deal — typically 3–5% — to meet regulatory skin-in-the-game requirements. Outside of that, it carries minimal credit risk and generates recurring, capital-light revenue by charging fees for underwriting, servicing, and structuring.

This approach allows Pagaya to scale efficiently without taking on much balance sheet risk or interest income dependency, making its revenue less volatile across credit cycles. In 2024, the company facilitated $9.7B in loans without directly issuing any under its name.

By contrast, Upstart operates as a vertically integrated, consumer-facing fintech. Borrowers apply directly via Upstart(.)com, and the company uses its AI models to assess risk and route applications to funding sources. These include partner banks (who may hold loans on their own books), institutional investors, ABS markets, and even Upstart’s own balance sheet — especially during times of weak demand.

This hybrid model gives Upstart more funding flexibility but also increases its exposure to credit and liquidity cycles. Historically, during periods of macro stress or weak investor appetite, Upstart has had to step in and fund a larger portion of loans itself, which can temporarily support revenue but increases earnings volatility and balance sheet risk.

While both firms are AI-native, Pagaya benefits from a broader and more diversified dataset, thanks to its integration with 30+ financial institutions across multiple asset classes. This shared architecture not only improves underwriting performance but allows for partner-specific customization.

Upstart’s dataset is narrower but derived from its own direct applicant funnel, giving it more control over the customer journey and potential for brand equity. However, this also makes it more vulnerable to reputation risk during periods of borrower stress or regulatory scrutiny.

In summary, Pagaya has taken a capital-light, infrastructure-led approach, acting as the operating system behind lenders. Its recurring fee model and reliance on private credit funding give it stability and scalability, especially during volatile cycles. That’s why, for instance, PGY’s revenue has consistently grown year after year, while UPST had to take its foot off the accelerator to address some tough issues from the past.

Upstart has made meaningful progress since the last cycle, particularly in reducing balance sheet exposure and increasing funding diversity. While its vertically integrated model carries more risk, it also offers brand control and long-term cross-sell potential.

Personally, I favor Pagaya’s model for its scalability and resilience — but it’s clear that Upstart has learned from past missteps and has worked hard to build a more durable platform. Both companies are contributing meaningfully to the future of AI-driven lending, just through quite different lenses.

What Led to Significant Mark-Downs on Retained Loan Tranches — And Why the Worst Is Behind Pagaya

After taking an initial look at PGY’s chart, you might be surprised by how volatile it has been since going public — and how far it now trades from its original listing price.

Pagaya’s business model, while capital-light in principle, involves a regulatory obligation to retain a small percentage of the riskiest portions (known as equity or junior tranches) of the asset-backed securities it creates. This requirement, typically 3–5%, is mandated under U.S. risk-retention rules.

In theory, Pagaya’s high-margin fee business (reflected by FRLPC margins) is designed to absorb any potential losses on these retained assets. But in practice, a combination of macroeconomic forces, strategic missteps, and poor capital market conditions during 2022–2023 exposed cracks in the model and forced the company to recognize significant write-downs.

Macroeconomic Backdrop: A Perfect Storm

At the heart of Pagaya’s impairments was the rapid and severe tightening of monetary policy by the U.S. Federal Reserve.

• Interest Rates: The Fed raised its benchmark rate from 0.1% in early 2022 to over 5% by mid-2023. The cost of capital soared across financial markets, including for ABS investors, who demanded far higher yields to compensate for rate risk.

• Credit Spreads Widened: As liquidity dried up, spreads on consumer ABS widened significantly. That meant investors would only buy ABS if the returns justified the risk — which in turn forced Pagaya to structure loans with thinner excess spreads (i.e., lower cushions for credit losses).

• Consumer Stress: The macro tightening began to strain U.S. consumers, especially in subprime segments, raising default risk on personal, auto, and POS loans.

Pagaya found itself in a bind. To keep growing its network volume, it continued underwriting and securitizing loans — but the market demanded capital structures that left almost no buffer for losses in the lowest-rated tranches Pagaya retained.

Structural Exposure to First-Loss Risk

By design, Pagaya holds the lowest-rated tranches in its ABS deals. These absorb losses first when borrower defaults occur. In a normal environment, this is manageable. But in 2023:

• The coupon paid to investors on senior ABS tranches was so high that Pagaya’s residual equity tranches yielded very little.

• Even modest levels of loan defaults were enough to wipe out the thin margins built into the retained tranches.

• In some ABS deals, Pagaya essentially earned the same return it was paying out, leaving no economic cushion to absorb credit losses.

As a result, the company had to write down the fair value of these retained tranches — a non-cash expense, but a very real drag on reported GAAP earnings and shareholders’ equity.

Cumulatively, over $400M in impairments were recorded across 2023–2024, primarily related to the 2023 loan vintage, which was originated under peak interest rate stress and contained structurally weaker credit protections.

Investors initially underestimated the severity and duration of these credit mark-downs. When the full scale became apparent, the stock plunged nearly 50% in two sessions after Q3 2024 earnings.

This was exacerbated by communication issues. Pagaya did not adequately flag the potential for continued impairments earlier in the year. The market interpreted this as a transparency problem, compounding concerns around model reliability and balance sheet risk.

Why the Worst Is Behind Pagaya

Despite the dramatic impairments and investor skepticism, several structural and operational improvements suggest that Pagaya’s most painful period is now behind it.

1. Runoff of Impaired 2023 Loans

The impairments were overwhelmingly concentrated in loans originated in 2023, which are now fully impaired.

No further large impairments are expected — a critical inflection point for GAAP profitability, which was just achieved in Q1 2025.

2. Improved Credit Performance and Tighter Underwriting

Pagaya has spent the last 18+ months upgrading its models and tightening credit standards. Some of the changes include:

• Increasing minimum applicant income thresholds (e.g., to $120,000).

• Requiring more employment stability and stronger cash flow patterns.

• Enhancing fraud detection through multi-partner data integration.

These upgrades have led to a 20–40% decline in delinquency rates for recent vintages compared to 2022.

3. Higher FRLPC Margins and Lower Risk Retention

Crucially, Pagaya has increased its FRLPC (Fee Revenue Less Production Cost) margin to a record 4.8% in Q1 2025 — up from 2.5% in 2022.

• This means fee income now exceeds risk retention, offering a profit buffer even if some retained assets default.

• At the same time, the company has successfully reduced its average risk retention to ~4%, down from 8–12% during the most stressed periods of 2022–2023.

This combination structurally de-risks the model and makes future impairments less likely and less severe.

4. Diversified Funding Channels

Pagaya has shifted away from relying solely on ABS. It now draws funding from:

• Forward Flow Agreements (e.g., with Blue Owl Capital)

• Pass-Through Securitizations

• Theorem Capital’s high-net-worth investor base

These funding sources often carry lower or no risk retention requirements, reducing balance sheet exposure and improving capital efficiency.

5. Self-Funding Status and Operational Efficiency

Pagaya’s model has reached a tipping point:

• It is now operationally profitable, with positive GAAP net income in Q1 2025.

This is exactly what triggered the 100% rally over the past two months: Q1 results gave the market confirmation that impairments had been fully recognized, paving the way for a clear path to sustainable profitability.

We’ll go over this in more detail later.

6. Management Mea Culpa and Enhanced Transparency

On multiple earnings calls and investor events, Pagaya’s leadership has publicly acknowledged past mistakes, including:

• Underestimating interest rate risk in 2023.

• Structuring ABS with insufficient credit cushions.

• Failing to guide the market early on about impairment risks.

In response, the company has overhauled its disclosure practices and reaffirmed its commitment to sustainable growth and credit discipline. Pagaya has consistently met — and even exceeded — its guidance in recent quarters, including delivering GAAP profitability in Q1, ahead of expectations for Q2 or Q3. If the company can continue to grow net income steadily, something that would even be accelerated with interest rate cuts, a market re-rating will likely follow.

All in all, the impairments that plagued Pagaya’s 2023–2024 financial results were not structural flaws in the business model but rather the consequence of poor capital market conditions, thinly structured deals, and execution missteps during a volatile period. Those vintages are nearly off the books, and all operational indicators — credit quality, FRLPC, risk retention, and funding diversity — are now pointing in the right direction.

With these headwinds largely resolved, Pagaya is entering 2025 with a clean slate, positioned to deliver consistent profitability, stronger capital efficiency, and scalable growth — restoring investor confidence and setting the stage for potential re-rating of the stock.

How Lower Interest Rates Enhance Pagaya’s Business Economics

Pagaya’s platform is uniquely positioned to thrive when interest rates fall. That’s largely because the company originates loans at relatively high, stable rates — typically above 20% — regardless of broader macro rate shifts. These loans are then structured into asset-backed securities, with the safer, senior tranches sold to institutional investors and the riskier, junior tranches often retained by Pagaya.

What makes this setup sensitive to interest rate movements is the return expectations of ABS investors. Typically, these investors demand a yield that’s a fixed spread — usually around 3% to 4% — above the 2-year U.S. Treasury rate. When interest rates are high, that spread becomes more expensive to fulfill. For example, if Treasuries yield 5.5%, ABS buyers may expect a total yield close to 9%. Given that Pagaya’s loan pool yields are relatively fixed, meeting that higher return expectation means the company must retain a larger share of the risky tranches — exposing it to more potential credit losses and capital strain.

Conversely, as interest rates decline, the yield hurdle for ABS buyers comes down. If the 2-year Treasury yield falls to 4.5%, those same investors might be satisfied with a total return of 8%, reducing the share of risk Pagaya needs to absorb. At even lower rates — say 2.5% — investor return requirements could fall further to around 6%, allowing Pagaya to offload more of the loan structure while retaining less capital-intensive exposure.

In practical terms, this means falling rates directly lower Pagaya’s funding costs and credit risk. With more of each loan package being sold off and less retained on its own balance sheet, the company frees up capital and improves profitability. The same loan yield now finances a greater portion of the structure externally — creating an operating environment that’s much more favorable.

Short Report from Iceberg Research

Iceberg Research published a short report in February 2025 alleging significant risks and losses associated with Pagaya’s investment funds, particularly the Opportunity Fund. The report suggests that Pagaya’s funds have absorbed substantial losses through risk retention of lower ABS tranches and investor redemptions, leading to questions about the company’s financial health and operational integrity.

Special thanks to @daardos on X for covering this so well.

Context and Key Facts

Pagaya operates several investment funds focused mainly on consumer credit, with the Opportunity Fund managing over $1B in assets as of mid-2023. These funds raised capital during a prolonged low-interest rate environment (2018–2021), which allowed Pagaya to deploy loans at relatively low rates. The rapid rise in interest rates from 2022 onward — driven by Federal Reserve monetary tightening — created a challenging scenario. Investors who locked in capital at lower rates began requesting withdrawals as market rates rose, seeking safer and higher-yielding alternatives such as government bonds and bank deposits offering over 5%.

Pagaya’s loan portfolio, however, was structured with longer-term loans issued at earlier, lower rates, restricting the company’s ability to instantly return cash to investors without disrupting loan repayments. Consequently, Pagaya implemented structured withdrawal limits aligned with loan cash flows to meet investor redemptions gradually, consistent with contractual obligations and industry norms.

Evaluating Iceberg’s Claims:

1. Investor Withdrawals and Losses:
   Iceberg’s core argument centers on investor dissatisfaction stemming from withdrawal restrictions in 2023. While this created short-term liquidity pressures, it was a widespread issue affecting many asset managers amid rising interest rates. No regulatory sanctions or lawsuits have materialized, indicating the actions taken by Pagaya were legally sound and consistent with fund agreements.

2. Losses on Investment Funds:
   The short report alleges massive losses absorbed by Pagaya-managed funds due to holding the riskiest ABS tranches. This claim is misleading. The funds have generated positive returns throughout their existence and remain profitable despite the challenging rate environment. The write-downs reported in 2024 relate primarily to risk retention on Pagaya’s own balance sheet rather than fund assets. This distinction is critical: the company’s equity bore the brunt of losses from junior tranche exposure, not the external investors in its funds.

3. Risk Retention and Fee Income Dynamics:
   Pagaya’s risk retention — its requirement to hold the most junior, highest-risk tranches — was notably high during the credit crunch (exceeding 7-10%), which pressured equity due to rising funding costs. However, since then, risk retention levels have decreased to around 4-5%, while the company’s fees for facilitating loan securitizations have increased to ~4.5%. This evolving fee-to-risk ratio suggests Pagaya is moving towards a more sustainable and profitable operating model where fee income covers retained risk exposure, reducing future write-down risk.

4. Regulatory and Legal Considerations:
   Despite Iceberg’s suggestions of imminent legal actions and regulatory investigations, no such proceedings have been initiated. The absence of lawsuits likely reflects the contractual clarity around fund structures and risk disclosures, as well as industry norms regarding liquidity management in fixed income and ABS funds.

In essence, the Iceberg Research short report appears to conflate Pagaya’s equity write-downs with fund performance and misinterprets the liquidity management challenges common to credit funds during an unprecedented interest rate hike cycle. The company’s funds remain profitable, and the write-downs affect Pagaya’s balance sheet risk retention, not the broader investor base.

Moreover, Pagaya’s proactive adjustments in risk retention levels, coupled with rising fee income, position the company well for improved profitability moving forward. The sustained support from major institutional investors and partners underscores confidence in Pagaya’s business model and strategic positioning.

Numbers

Pagaya Technologies kicked off 2025 with a clear financial turning point, marking its first quarter of GAAP net income profitability and delivering across virtually all KPIs. The company’s Q1 2025 results not only exceeded internal and Street expectations but also confirmed its transition into a self-funded, highly efficient operating model with strong earnings momentum.

Network Volume

Pagaya reported $2.4B in network volume in Q1 2025 — flat YoY and slightly below its $2.5–$2.7B guidance. Importantly, this shortfall was intentional, driven by a strategic decision to reduce Single-Family Rental (SFR) loan volumes, which generate the lowest fee margin in Pagaya’s mix.

Crucially, excluding SFR, total volume actually grew 26% YoY and 6% QoQ, with robust contributions from personal loans, auto lending, and point-of-sale financing. The conversion rate on loan applications held steady at ~1%, in line with the 3-year historical average, showing that the company's underwriting discipline remains intact even as loan volume composition shifts.

Revenue Growth

Total revenue and other income hit a record $290M, up 18% YoY, and landing at the upper end of guidance. As usual, fee revenue made up the vast majority, reaching $283M (up 19% YoY) and driven by:

• Volume growth in personal loans and auto loans.

• Higher FRLPC per loan, reflecting mix shift and pricing optimization.

• Increasing monetization of embedded partnerships.

Non-fee income — including interest and investment returns — was flat at $7M, underscoring the company’s shift away from balance-sheet-dependent income streams.

FRLPC

The most important operational profitability metric, Fee Revenue Less Production Costs (FRLPC), came in at $116M, up 26% YoY. The FRLPC margin (FRLPC as a % of network volume) hit a record 4.8%, up 100 bps YoY. When adjusted for the absence of low-margin SFR loans, the FRLPC margin jumps to 5.2%.

The quality of Pagaya’s revenue is improving:

• In Q1 2025, 77% of FRLPC came from lending-partner fees, vs. 63% in Q1 2024.

• Investor-side fees now make up just 23%, down from 37% YoY — a sign of Pagaya’s reduced reliance on capital markets execution and a tilt toward more recurring, embedded tech integration revenue.

This mix shift is crucial: lending-partner FRLPC is stickier, higher-margin, and less volatile than investor-related fees. It also signals increasing adoption and dependence on Pagaya’s embedded infrastructure by financial institutions.

Segment-Level Unit Economics

Pagaya’s disclosed FRLPC margins by vertical reinforce the margin accretion:

• Personal Loans: 5.8% FRLPC %

• Auto Loans: 6.4% FRLPC %

• POS: not disclosed but scaling rapidly

Auto loans in particular benefited from improved credit performance, higher vehicle values, and better execution in funding structures.

EBITDA and Profitability: Operating Leverage Kicks In

Pagaya generated record adj. EBITDA of $80M, up 100% YoY, translating into a 27% EBITDA margin, up 11 points from 16% a year ago.

Importantly, the company’s incremental adj. EBITDA margin — essentially its flow-through on new revenue — hit 89%. This means that 89% of new revenue went straight to EBITDA, highlighting the enormous potential for operating leverage in this business model.

Just look at the chart below to see the clear trajectory.

• Core operating expenses as a % of FRLPC dropped to 38%, the lowest in company history.

• Operating income was $48M, up from $7.7M YoY.

• Operating cash flow totaled $34M, further demonstrating cash generation capacity.

This margin expansion validates Pagaya’s asset-light model: its cost base does not scale linearly with volume, allowing the company to unlock profitability at modest growth rates.

GAAP Net Income and Adjusted Earnings

After years of losses driven by retained tranche impairments, Pagaya posted GAAP Net Income of $8M, an improvement of $29M YoY. This beat guidance (which had projected breakeven to a $20M loss) and signaled a clean earnings profile.

• Adj. Net Income was $53M, which strips out non-cash items including:

$13M in stock-based compensation
$24M in fair-value adjustments on retained ABS tranches
$6M in whole-loan impairments

These credit-related losses are now largely behind the company: impairments tied to the weak 2023 vintage are fully recognized, and the balance sheet now reflects healthier vintages from late 2023 and 2024.

Credit Performance: Stabilization Confirmed

Pagaya’s underwriting performance continues to improve:

• Personal Loan 2023 vintages: Cumulative net losses (CNLs) are 20–40% below 2021 peak levels.

• Auto Loan vintages: CNLs are 30–50% below 2022 peaks.

Improved outcomes reflect tighter underwriting (e.g., higher income thresholds), expanded partner datasets, and more diversified funding structures that enable better loan structuring.

Funding & Capital Structure: De-Risked and More Efficient

Pagaya’s funding model continues to evolve toward lower capital intensity:

• Raised $1.4B in ABS during Q1 across 3 transactions.

• Signed a $2.4B forward flow agreement with Blue Owl, and maintains another with Castlelake — bringing total forward flow capacity to $3.7B.

• Non-ABS channels (e.g., pass-throughs, private funds) expected to make up 25–50% of 2025 funding volume.

This shift reduces risk-retention exposure (targeting 4–5% vs. 8–12% in 2023) and aligns with the company’s self-funding goals.

Balance sheet strength:

• Cash and Equivalents: $230M, fully covering total current liabilities of $198.7M

• Investments in Loans/Securities: decreased to $760M, mostly risk-retention assets

• Net fair value adjustment in Q1 was $45M, down from $156M in Q4 2024 — suggesting stabilization in retained asset valuations

Management reiterated that no equity raises are planned, increasing confidence in the durability of profitability across credit cycles.

2025 Outlook (Raised)

Conclusion: A Turnaround Validated by the Numbers

Pagaya’s Q1 2025 results represent a decisive inflection point. After two years marked by market skepticism, credit-related impairments, and macro headwinds, the company has now emerged with clear evidence that its business model is not only structurally sound, but also increasingly profitable.

The key takeaway: Pagaya is monetizing loan volume more efficiently than ever before, with FRLPC margins hitting all-time highs, operating leverage expanding, and GAAP profitability arriving ahead of schedule. And it’s doing so while reducing balance sheet risk, diversifying funding, and deepening partner integrations — all without relying on dilution or external capital.

The financials underscore a powerful narrative already explored throughout this report: Pagaya isn’t a lender, it’s an infrastructure layer — a modular, data-rich, AI-driven platform that quietly powers credit access for banks, fintechs, and institutional investors alike. The shift from investor-driven revenue to partner-driven economics is accelerating, and the model is proving it can scale without adding fragility.

If the worst of the impairments are truly behind — as results suggest — and execution remains disciplined, Pagaya has not just recovered from past volatility, it has reset the foundation for sustained earnings growth. The business is operating with more capital efficiency, risk awareness, and margin strength than ever before.

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