Pagaya: 3× Upside But On Thin Ice

Pagaya has a massive growth potential ahead but it comes with lethal balance sheet related risks.

Oguz Erkan

Oct 19, 2025

Let me start with a question—why was the internet so revolutionary?

Because the internet achieved two things:

Infinite scale.
Instant access.

Thus, resources and services that were previously hard to reach have become increasingly accessible.

This is the hallmark of the digital era: Democratization of access.

Naturally, most successful companies on the internet are those that democratize access to products, services, and skills.

Google democratized access to knowledge; social networks democratized access to fame; Amazon enabled people to open their stores and reach millions of customers at a fraction of the cost of opening a physical store, etc.

How did those companies achieve it?

Most people would think that they created a new supply. Amazon created a new supply of goods on the internet, for instance. This is true, but this isn’t what made Amazon the giant we know it is today. There is something that differentiates it from a big e-commerce shop.

Amazon’s main success came when it enabled third-party sellers to operate their own stores on the Amazon marketplace.

Today, 62% of all the goods sold on the Amazon marketplace are sold by third parties:

What does this tell you?

Well, among other things, it tells me that in the absence of the third-party sellers, there will be a giant strain on Amazon to bridge all the supply gaps.

This is the real source of success in the digital era.

The most successful companies of the digital era democratize access, but they don’t do it by creating the supply themselves; instead, they build mechanisms that meet the idle supply with the demand.

I heard this from Travis Kalanick himself at a conference at UCLA.

When asked what made Uber go from a premium taxi company to a mobility giant, he said this: “The critical insight was that there was no shortage of taxi supply, but the supply was extremely idle. We basically decided to meet the idle supply with demand.”

Remember, in the past, most of the taxis stopped on the corners for customers to see them, or they were roaming the streets looking for customers. This created a mismatch between the demand and supply and made it look like there was a shortage, even though they were not. The real case was that most taxis were idle, waiting for customers to see them.

The same goes for Airbnb. The shortage of accommodation, if it existed, was significantly lower than perceived because most people who were willing to rent out their apartments or free rooms for short stays lacked a convenient way to do so.

The supply was idle.

Companies like UBER, Airbnb, Amazon, etc, heavily tapped into this idle supply.

When the idle supply is mobilized, it has one obvious result— it awakens the dormant demand.

There are a lot of people who are withholding themselves from demanding a good or service just because they think it’s hard to access. Thus, the mobilization of idle demand and easier access awaken the dormant demand.

Result? Demand and supply grow together, rapidly growing the market.

Thus, those companies that initiate these processes grow beyond their expectations.

Though industries like mobility, hospitality, and commerce have experienced rapidly democratizing access, the process has been way slower for some industries. Arguably, this is where many opportunities still exist.

Finance, especially consumer credit, is one of those markets where there are massive opportunities for democratizing access.

Access to credit is currently extremely tight.

According to the Bankrate Survey, 48% of loan applicants were rejected last year.

It’s absurd to think that all those people were unworthy to extend credit. The problem is that credit is still largely supplied by the banks. This keeps the credit unduly tight for two reasons:

Most banks don’t look beyond FICO scores.
Banks’ risk appetite tends to be lower as they assume balance sheet risk.

Banks shouldn’t just avoid risk itself; they should also avoid the perception of risk, which can then cause a run on a bank and lead to the collapse of the institution.

Thus, they are designed to categorically reject the opportunity to make more money by taking a bit more risk.

However, outside the banking system, there are investors who can accept the risk posture banks rejected because they don’t need to fear things like a run on a bank, etc.

Yet, they haven’t had an institutionalized way to tap into the consumer credit market, nor have consumers had easy access to these capital sources. The classic idle supply and unmet demand situation.

Pagaya is trying to bridge this gap.

Its product meets the loan demand that can’t be met by the primary sources, with alternative capital that may be willing the fund the loan, increasing access to credit.

This is a huge market, given that a total of $250 billion worth of personal loan applications were rejected last year. Add these auto loan BNPL rejections, and the total addressable market will be massive.

So, how does Pagaya address this gap, and does it make sense to invest in it now?

Let’s dig!

What are you going to read:

1. Understanding The Business

2. Competitive Analysis

3. Investment Thesis

4. Fundamental Analysis

5. Risks

6. Valuation

7. Conclusion

🏭 Understanding the Business

I have been observing this company for a while now. I was first urged to take a look at it by members in our Discord community.

I took a look, liked the business, but delayed the write-up so far because it was skyrocketing in price, and I already had other deep dives scheduled.

Yet, in the meantime, I talked about this business with some other people who were very hyped about it and had an investment. The question I always asked was—what does it do? How does it actually work?

Here are some answers I got:

“AI-driven underwriting platform.”
“AI-powered liquidity network.”
“AI-driven lending network.”

This is what they internalized from the slide below:

To my ears, these are bunch of bullshit.

These are packaged buzzwords made up to make the business both ununderstandable and create FOMO at the same time. Because this is how people act. When they see something they don’t understand and is packaged with the latest buzzwords, they instantly get FOMO. We feel like it’s so ununderstandably complex that it should be so good and become so big.

This is exactly how people go bankrupt.

The business ecosystem is getting increasingly complex. As the broader opportunities dry up, companies tap into hidden opportunities that are necessarily harder to understand. This is further elevated by the integration of AI systems and AI-enabled opportunities.

Thus, the path should be to disentangle the business structure and simplify it as much as possible, rather than increasing the complexity by fitting the whole business into buzzwords like AI-driven underwriting platform, as in the case of Pagaya.

So, let’s unpack it, shall we? What the hell is an AI-driven underwriting platform?

Let’s take a step back and go to basics—how do the bank loans work?

It’s simple. Banks collect deposits by offering interest. They lend the money they collected at higher interest rates, making money on the margin.

Here, they are exposed to two main risks, one is visible, and one is invisible.

Credit risk.
Systematic risk.

Credit risk is straightforward. If the bank loses money on the loans, it’s basically using up client deposits. Normally, banks are able to absorb this seamlessly, as not everybody needs their money at the same time.

However, if the trust in the system erodes for some reason, like somehow people think banks are unsafe, everybody may try to withdraw money at the same time, which depletes the bank’s cash on its balance sheet and leads to insolvency. Thus, banks should avoid both the credit risk and the risk of being perceived as unsafe.

Thus, by design, banks have lower risk tolerance on credit than what would be acceptable for a private lender.

Result? They have tight lending standards that exclude many borderline cases that would be acceptable for private lenders.

Most of the time, rejected people don’t have access to this alternative capital, so they remain underserved while private lenders end up missing many lending opportunities.

In other words, there is a gap between alternative capital and borderline rejects.

Pagaya bridges this gap.

How does it do this?

Well, Pagaya’s platform sits between the lenders and investors:

Lenders are banks, fintech platforms, private lenders, etc. Generally, they are in the lending business themselves, so people apply to them for loans.

Investors are the outside investors who may be willing to lend money to the borderline cases that the lenders reject. Because they are exposed just to the credit risk and not the systemic banking risk, their risk appetite may be higher.

Pagaya’s platform connects these two parties together.

It raises money or gains access to a warehouse credit facility that it can use to issue loans to the people who meet certain criteria. It does this by its underwriting platform powered by AI.

On the other side, it connects this platform to the lenders’ tech stacks via its API. Thus, when a lender rejects an application but thinks it may deserve a second look, it sends it to Pagaya through the API. The Pagaya platform evaluates the application based on the AI model and approves the loan if it meets the criteria, and notifies the lender through API. In that case, the lender looks like it approved the application, but it’s actually the third-party investors who fund the loan.

In such a model, money can flow from outside investors to borrowers in three ways:

Warehouse facility.
Pre-funded special purpose vehicles (SPV).
Pass-through and forward-flow-like arrangements.

In the warehouse model, the sponsor can create an SPV that has access to a warehouse credit facility. When the sponsor approves a second-look loan, the lender originates the loan, and the sponsor purchases it from the lender through SPV, which uses the warehouse credit facility to pay the lender. When the loan pool in the SPV reaches a certain point, the SPV securitizes the loans and sells the bonds to capital market investors. SPV pays the warehouse lenders back, repeating the process.

In the pre-funded model, the SPV is seeded with capital by investors from the start. SPV raises the capital by promising investors that it’ll make money by lending to people meeting certain criteria and paying regular interest + principal to them. Investors put the money in and receive the bonds from the start. When Pagaya approves borrowers and SPV buys the loans from the lenders, investors get regular interest + principal payments.

Pagaya’s SPVs are generally pre-funded:

Other than pre-funded SPVs, it also uses forward-flow and pass-through arrangements. In the forward flow model, the buyer agrees to purchase loans approved by Pagaya up to the agreed cap. In the pass-through model, Pagaya aggregates loans in one trust and passes them to an investor.

This results in a capital-light model where Pagaya earns 4-5% fees on the originations and holds 5% of the loans on its balance sheet, as the Dodd-Frank Act of 2010 requires asset-backed security (ABS) sponsors to carry at least 5% of the credit risk.

It works amazingly because it’s a win-win model for all stakeholders:

More borrowers get access to credit.
Lenders approve more of their clients, maximizing retention & satisfaction.
Investors put their money to work without doing risk control by themselves.

While doing all that, Pagaya makes money. Everybody is happy.

Such businesses that make all the stakeholders happy are rare, but when they do appear, they tend to work extremely well for the long term.

So, in short, we are looking at a business that:

Identified a real gap between supply and demand.
Devised the right business model to address it.
Makes all the stakeholders happy.

What’s even better than all these is that Pagaya’s business model is conducive to durable competitive advantages.

This is what differentiates it from most other names in fintech. Given the low entry barriers, it’s really hard to create a durable moat in fintech. However, Pagaya has found a niche market and combined it with a business model, creating a business that is resistant to losing business to competition.

🏰 Competitive Analysis

I have analyzed thousands of companies both for investment purposes as an analyst and for research purposes as a competition economist.

Here is what I found—there are limited sources of competitive advantage.

Most of the time, competitive advantage stems from five sources:

Brand power.
Network effects.
Barriers to entry.
Local economies of scale.
Government regulation.

However, there is an unlimited number of competitive advantages.

What the hell does this mean?

Just like technology, competitive advantages are modular, i.e, they can be disassembled and reassembled again in all kinds of ways.

Sometimes, the business may not strongly benefit from any of these sources of competitive advantage, but the ways and magnitudes it benefits from them can come together in such a unique way that, together, they create a durable advantage.

This is generally referred to as “lollapalooza moat” among investors.

It references the term “lollapalooza effect” coined by Charlie Munger, which refers to a situation where multiple biases, tendencies, or mental models act in concert to produce an extreme outcome.

Interestingly, what I observed in analyzing and following Pagaya is that the way it builds its competitive advantage follows the lollapalooza dynamic, but it’s structurally different.

Instead of combining many different but not particularly strong competitive advantages together, it benefits from the same competitive advantage at modest magnitudes several times and at different touchpoints.

What the hell does this mean?

Pagaya doesn’t benefit from many competitive advantages, which is endemic to fintech businesses.

Economies of scale aren’t much relevant when the input is capital itself.
Brand power doesn’t mean a thing in B2B, especially in finance.
Entry barriers aren’t that high; capital is generally abundant.
Government regulations are equally permissive to all.

However… It benefits from network effects.

This is the natural result of its positioning between the lenders and investors:

Naturally, it’s a two-sided network. One side of the network is lending partners, while the other side is investors.

Thus, it benefits from both direct and indirect networks.

As it grows its lending partner network, more lenders want to team up with Pagaya as they also want to bump up their approval rates. (Direct network effects)
The more lenders it teams up with, the more investors follow as they want to tap into these higher-quality subprime borrower pools. (Indirect network effects)

These are the obvious ones, but there is more. As it drives partner satisfaction, the number of touching points for network effects increases.

Once its lending partners satisfy their clients, they see:

Faster new client growth.
More clients return for the second loan.

As a result, the overall loan applications they receive grow rapidly, also growing the number of applications forwarded to Pagaya, which drives network volume growth.

Another touching point is on the investor side. As they drive results, they don’t just attract new investors, but also attract more capital from the existing investors.

Another touching point where network effects drive better performance is data and AI capabilities.

The more applications it processes and the more results it follows, the more valuable data it gathers, which is then used to develop its AI models and underwriting process.

This is called data network effects:

As you see, I have listed 5 touching points in a limited space:

Direct network effects attract more lenders.
Indirect network effects are driving investor growth.
Additional network effects on the lender side, driving client growth.
Additional network effects on the investor side are driving volume growth.
Data network effects are used to develop the product, driving all of the above.

Now, here is the thing—none of these network effects is strong enough to make it untouchable.

Compare it to the network effects that Meta enjoys, for instance. They are so strong that they are enough to make it untouchable. For Pagaya, this is not the case primarily because it’s operating in a B2B market where there is are limited number of players and players are exponentially more rational.

However, when they come together, they create a strong system of network effects that is enough to restrict the strategic choices of its competitors.

I call this “lollapalooza network effects”, inspired by the lollapalooza moat:

Any competitor trying to penetrate its market will likely think that it can penetrate through any of these touchpoints. However, the broader system protected by the combination of these network effects is exponentially more powerful than its aggregate suggests.

On top of this, the number of available lending partners in the industry is a limiting factor. Pagaya is already working with some of the biggest personal loan issuers in the nation, such as SoFi. These partners are unlikely to dump Pagaya for another competitor, as it exposes them to unnecessary operational risk, provided that Pagaya already drives satisfactory results. ➡️ Operational switching costs.

The same limitation exists on the investor side, too, though to a lesser extent. Providers of alternative capital like to spread their bets, but there are some points where they feel like they are overexposed to the same asset class or business model. This is why they are unlikely to work with too many of Pagaya’s competitors at the same time. ➡️ Portfolio switching costs.

In sum, Pagaya has several competitive advantages that make me believe that it can grow its business consistently and reliably in the future, which is a rare occurrence in its industry. It benefits from multiple small to moderate-sized network effects at the same time, digging a relatively deep moat around the business when combined with operational and portfolio switching costs.

It’s hard to find a business as well-positioned against competition as Pagaya in the fintechs.

📝 Investment Thesis

Pagaya is so well-positioned in the industry between the unmet demand and idle supply that the investment thesis makes itself obvious. It relies on three key pillars:

➡️ Huge Addressable Market

Last year, 6.3 million new personal loans were originated in Q4, according to TransUnion, with the average loan size of nearly $7,000. Annualizing these numbers gives us 25.2 million total originations and $176 billion total new personal loan origination volume for 2024.

Bankrate suggests that nearly 50% of all loan applications were rejected last year, and rejections for personal loans reached 38% for personal loans according to Lending Tree.

What strikes me most is that the blend rejection rate for all financial products among Gen Z is currently at a neckbreaking 65%.

This means that those who lack or have limited credit history are the ones who struggle most to access credit.

It would be a mistake to consider those people unworthy of credit as a group. The problem is that they lack a credit history, which limits their access to even starter loans, given that banks have tightened their conditions significantly since the mini banking crisis in 2023, and they haven’t eased much, as they aren’t confident about the continued rate cuts.

Another issue is that these are young people who got their first credit cards, possibly in college. They might have missed a few payments, taking down their credit scores. However, this doesn't reflect their true financial power as new entrants to the workforce. In short, though not for banks, a substantial portion of these people could still be considered relatively safe for private lenders.

So, how many of these people are really worthy of credit?

According to the landmark NBRE research, new AI-based lending models may result in safely approving 15-30% of people who would have been rejected by traditional underwriting models. Most of those people are “invisible primes”, borrowers with low credit scores and short credit histories, but also a low propensity to default.

So, even if we assume that just 20% of all those people are safe to lend to, we end up with approximately $22 billion incremental origination volume for personal loans.

The same arguments can be made for auto loans and Point of Sale (POS) loans, the type of loan Buy Now Pay Later (BNPL) providers like Klarna deal with:

Auto Loans in 2024: $700 billion origination, 11% rejection rate.
POS Loans in 2024: $100 billion origination, %20 rejection rate.

Pagaya sees this.

They entered auto loans in 2021 and POS loans in 2023, massively expanding the pipeline they can tap into:

Based on 2024 numbers, even if we assume that just 15% of rejected auto and POS loans were safe to lend, it potentially means nearly $22 billion additional network volume.

Add $22 billion volume from personal loans, and we reach nearly $44 billion network potential for Pagaya, on conservative assumptions.

This excludes the organic volume growth. Assuming 5% blend growth rate for originations across three loan types and we’ll get $56 billion potential network volume in 2030.

This is only for the US.

They can easily expand to Canada, and even better, Latin America, where access to credit remains highly restrictive.

In short, there is a huge market potential ahead of Pagaya, and it’s very well positioned to take advantage of this, given its market position and multi-layered network effects protecting it.

➡️ It will rapidly grow the partner network.

There are two primary drivers of growth for Pagaya:

Investors.
Lenders.

There are two sides to its network. Pagaya needs to grow at least one of them to drive volume growth. It’s best if it grows both of them at the same time.

Currently, they are aggressively trying to grow their lending partners.

They are in talks with 80% of the top 25 US banks and are targeting to add 2-4 lending partners going forward. Given that they currently have just 31 lending partners, there is a very long pipeline it can tap into going ahead. Even if it adds just a few partners every year, it can drive significant network growth when combined with organic volume growth from its existing partners.

Growing a partner network would normally be a great operational risk. We are seeing this with SoFi’s Galileo. Despite the high hopes from the segment, it constantly lags behind the rest of the company due to its inability to add new partners. However, I don’t think this is the case for Pagaya. Its product doesn’t expose the lending partner to an additional risk; to the contrary, it helps partners to maximize satisfaction. It’s a win-win product. Thus, I believe it can reliably and consistently grow its partner network going forward.

At the investor side, Pagaya is firing on all cylinders.

They are already the #1 personal loan ABS issuer in the US, and they have been rapidly growing their investor base.

They had around 20 investors in their network at the end of 2020, which grew to over 140 last quarter. The rapid growth of the investor network proves that they are driving real ROI for the investors.

Its solid results will attract partners to both sides of the network, which will grow the network volume and thus revenue.

➡️ Take rates will grow as Pagaya drives ROI.

Pagaya currently earns a 4-5% fee revenue less production costs (FRLPC) on the origination volume.

There are two things to focus on here:

Its fee revenue as a percentage of loan originations is steadily increasing.
Fee mix has shifted from funding partners to lenders.

What does this tell us?

Well, it confirms what we already know—much of the value creation happens upstream at the point of approval.

Once banks realize that they can bump their approval rates without incurring extra risk by utilizing Pagaya’s technology. This means:

Higher conversion rate and thus lower customer acquisition cost.
They more easily hit volume & mix targets.

On top of those, if the lending partner thinks the potential ROI and risk posture is attractive, it’ll surely want to keep more assets on the balance sheet and generate incremental interest income. If it offloads the loan balance to an SPV sponsored by Pagaya (this is what happens now), it’ll get instant capital relief and keep the origination fees.

Meaning, the model offers a no-lose case to lending partners, which is why the revenue mix shifted upstream.

This already validates the value proposition of Pagaya. I believe it’ll be able to raise its fees as more value it drives to the partners and the more its product becomes integral to their partners’ operations, especially the lending partners.

Further, while Pagaya’s network is primarily originate-to-distribute today, it’s plausible that, as model performance seasons and funding/capital conditions favor on-balance-sheet growth, some partners may start retaining a portion of loans they originate. In that scenario, Pagaya can justify higher lender-side fees tied to the incremental risk-adjusted yield the bank keeps—potentially lifting overall take-rates even as funding-side fees diminish.

In sum, Pagaya is growing into a huge market, and it has only tapped into a small portion of it.

There is much room for growth in the existing loan categories. Beyond that, expansion into new categories and geographies is possible.
It has a very long pipeline for potential partnerships, which will drive volume & fee growth going forward.
Finally, it can expand its FRLPC as a % of net loans as its product drives more and more value and becomes more embedded in the operations of the partners.

It is as well-positioned as it gets to exploit these opportunities going forward.

📊 Fundamental Analysis

➡️ Business Performance

I think all it gets is one word to summarize Pagaya’s performance—phenomenal.

This company literally grew its operating revenues by 10x in just 5 years. This indicates not just top-level execution, but also incredible product-market fit. The company is tapping into an obvious gap in the market where growth feels effortless.

This is a mind-blowing growth, but it didn’t come at no cost. As we’ll see below, it might have unduly eased credit conditions between 2020-2023 to fuel growth as impairments skyrocketed from 2023 to 2024.

Still, given that the business is about to come out unscathed from that period and turn GAAP profitable, we can appreciate this mind-blowing growth. Yet, we’ll see below that there was a cost to it.

➡️ Financial Position

Well, analyzing the balance sheet isn’t easy for a company that is operating through complex lending structures and holds a portion of the loans on its balance sheet.

There are three reasons for this:

Its expected impairments depend on whether the consumer remains strong.
If the system starts to crack, access to capital may close, and it may have to take losses against its equity pool.
In a low liquidity environment, its operations may not be self-sufficient.

I’ll dive deeper into these factors in the risks section below, so I’ll give a surface-level snapshot here to not make things overly complicated under this sub-section.

During Q2 2025, the company had a principal long-term debt of $332 million and a total of $267 million in secured borrowings. Both have high interest rates at 11.95% and 15.14% respectively.

After the closing of Q2, they issued new $500 million senior notes with an average interest rate of 8.875% and paid all $332 million long-term debt and $58 million of secured borrowings.

As a result, $209.5 million of the secured borrowings still remains, and the pro-forma debt of the company totals $709.5 million with the addition of the new senior notes.

However, the table doesn’t include $147.5 million of exchangeable notes. They are debt until exchanged as they carried an effective rate in the high single digits, so the real total debt is $857 million.

Against this, the business holds just $468 million of equity in its balance sheet, and TTM EBITDA is just $161 million.

Well, this is leveraged.

I would want to see better debt coverage given that Pagaya holds junior slices of its own deals and finances part of them with costly borrowing, a downturn can hit both sides at once—higher credit losses and expensive carry. Meaning, if the credit and market conditions deteriorate more than expected, the company will have very limited maneuvering room.

I loved how this business performed in the last 5 years; however, I can’t say I appreciate this balance sheet.

It’s a yellow flag for me.

➡️ Capital Allocation

Measuring the quality of capital allocation is another challenge in companies that make money by manipulating financing vehicles.

Traditionally, we measure the capital allocation performance by looking at return on equity or investment, or we look at the sales to capital ratio if the company is unprofitable, as Aswath Damodaran suggests.

Pagaya presents two challenges:

It’s unprofitable on the TTM GAAP basis.
Its binding capital isn’t property and equipment in the traditional sense.

What would be the invested capital for a company like Pagaya?

Well, given that it’s making money by generating fees and interest income based on the loan assets it holds in the balance sheet, I would say the most precise measure would be how much of its own capital is tied to support the loan assets held in the balance sheet.

As of today, it holds $870 million of long-term investments in its balance sheet.

$195 million of that is financed by risk retention repo, meaning that other investors are holding $195 million of that debt currently. This means that $695 million of its own capital is tied to support the loans carried in the balance sheet.

Against this, it generated $1.1 billion in fee revenue in the last twelve months.

This means that its sales-to-capital ratio is somewhere around 1.6, meaning it’s generating $1.6 revenue for every $1 tied to operations.

This is a satisfactory number, illustrating that it’s making efficient use of its capital.

🚨 Risks

I believe there are two primary sources of risk for Pagaya—systematic and operational.

1️⃣ Systematic Risk

Systematic one is pretty straightforward. Its business is driven by the credit cycle. When interest rates rise and credit tightens, its business will inevitably be affected.

We recently experienced this back in 2023.

It grew operating revenues nearly 7x from $91 million in 2020 to $685 million in 2022. In 2023, operating revenue growth plummeted to 12% as the Fed implemented the fastest rate hikes in history.

There is no way to avoid this. If credit tightens, it’ll slow down.

So, the question is simple—where are we in the credit cycle right now?

It’s hard to say..

CCC credit spread is around 8% today, which could be considered cautiously optimistic.

Investors are neither showing too much tolerance to weak borrowers nor are they being too restrictive. We haven’t seen a definitive dip in the spread where money might have flown to weak businesses, brewing the conditions for systemic defaults.

So, I would say the current credit conditions look sustainable in themselves, but there are too many events that can disrupt this balance, like tariffs, uncertain inflation projections, Fed policy, etc..

However, for now, I would say credit looks healthy. In the last two recessions, excluding Covid, CCC spread had dipped below 6%, paving the way to systematic defaults. If the CCC spread falls below 6.5%, I’ll probably start thinking that investors are acting carelessly and will be more cautious for credit-based business models like Pagaya, but it looks alright for now.

2️⃣ Operational Risks

I will divide the operational risk into two parts.

The first one is the risk associated with its business model and execution, i.e, its business model’s ability to drive satisfactory performance for stakeholders. This is largely tied to its underwriting performance, thus to its technology.

The second one is deeper—balance sheet risk. This is the risk it takes on the balance sheet to grow operations. Though this is closely connected to the systematic credit risk, it’s different because bad balance sheet management can still lead to the demise of the business even if the market-wide credit conditions don’t deteriorate to alarming levels.

So, let’s dig..

➡️ Business Model Risk

Well, the biggest operational risk I see is its ability to keep driving alpha for both lenders and funding partners.

Pagaya’s product is very easy in terms of measuring performance. If it drives incremental loan volume that is profitable from a reject pool, it’s driving alpha.

This depends on two things:

The overall quality of the rejection pool.
Performance of its AI model.

The first one is largely out of its control, and it’s driven primarily by the systematic factors. It controls the second one, and I think it’s as well-positioned as it could be for sustained performance here. Its model benefits from serious data network effects, which lead to improved performance with every additional application it processes. As long as this remains the case, I don’t think any lending partner will consider dumping it for another provider.

This is illustrated by its 100% net lender retention rate since inception:

As it keeps those partners and adds new ones, its processing volume will keep increasing, and its underwriting model will further improve. Thus, operational risk substantially reduces over time rather than increasing.

➡️ Balance Sheet Risk

Here is the thing—Pagaya buys the junior tranches of its securitizations to hold on the balance sheet.

It should be intuitive to everybody.

If you are an ABS sponsor, you need to hold at least 5% of the credit in the balance sheet under the Dodd & Frank Act. This requirement can be met horizontally by buying 5% of the first loss tranche, or by 5% of each tranche, or by a mix of both.

If you are selling these securities to investors, they will want to buy the most senior tranches, and they’ll want to see you buying the junior tranches to show confidence. Thus, many ABS sponsors (including Pagaya at times) use a horizontal piece because it aligns interests and is operationally simpler.

Today, it holds $870 million of debt credit risk in its balance sheet under “Investments in loans and securities.”

Securitization notes and FVO notes refer to the senior, safer tranche; while securitization certificates and FVO certificates refer to the junior tranches.

Thus, today it holds $547.1m of junior securities and $321.2m of senior securities.

Amortized cost for junior certificates was $1.045 billion.

This means that nearly 47% of them are already recognized as a loss, while senior notes remained largely intact.

Here, the risk is that if the underlying loans perform worse than Pagaya expects, they will start eating away at its equity.

Here is a quick scenario of how further markdown on certificates may affect Pagaya’s equity:

As you see, a 40% further markdown on certificates effectively wipes half of Pagaya’s equity.

So, what’s the likelihood that this may happen?

Well, it’s not impossible.

Markdowns previously went from $98 million in December 2023 to $508 million in December 2024, a staggering 5x increase. This was largely because of the weakness of the 2022-2023 vintage, as these were the loans issued at higher rates while the consumer was struggling.

Given that the Fed hasn’t hiked interest rates since then and further cuts are possible from here, I don’t think it’ll go much worse than that. Still, it may make some additional markdowns as late 2023 and early 2024 vintages mature, but these can also be offset by growing fee income.

Overall, balance sheet risk is there, and it’s a real one as the business previously absorbed large losses. However, the market conditions have improved substantially since 2023, and the business itself is also nearing GAAP profitability, so I don’t think it’s an imminent risk.

Still, if you are investing in this company, you should always keep your eyes on the credit market and Pagaya’s balance sheet. In short, there are risks, both systematic and operational; however, the current conditions favor more optimism rather than pessimism, I believe. Yet, investors should keep in mind that this is a business playing with complex financial instruments, and your visibility into the operations will be naturally lower. It would probably be wise to assume that it’s always in a less attractive situation than it looks on the surface.

📈 Valuation

I have said this many times, and I’ll say it here again—valuation is easy if the business is a predictable one; it’s impossible if it’s an unpredictable one.

If you are trying to value an unpredictable business, you are basically speculating because you are trying to discount risks that can’t be accurately assessed, given the unpredictable nature.

Conversely, if you are looking at a predictable business, you just need conservative assumptions and then run the numbers.

What makes a business predictable?

Market and its position in the market.

If the market is big enough and the business has durable competitive advantages, you can expect it to consistently grow into that market, abusing its competitive edge.

Pagaya has this.

It benefits from multiple network effects at different touchpoints, creating significant exit barriers for all partners and attracting new partners. This is illustrated by its 100% lending partner retention and consistent growth of funding partners.

Thus, all we need are conservative assumptions.

So, how much can it grow in the next 5 years?

It grew, on average, at a 65% annual rate in the last 5 years, and it’s set to grow around 25-30% this year.

Even if we assume that it can grow only 20% annually in the next 5 years, we’ll end up with $2.7 billion in revenue in 2030.

Given that the mature companies in the lending network business have around 10-20% net margin, we can assume that Pagaya will also have 15% net margin. This means that it’ll generate $405 million in net income in FY 2030.

Slap a conservative 15x earnings multiple, and we’ll have a $6 billion company.

It’s currently valued at just $2 billion, meaning it can make 3x in the next 5 years even under conservative assumptions.

🏁 Conclusion

Pagaya is a complicated business.

It has some of the virtues that I truly love, like multiple network effects, strong growth, industry position, etc.. These enable it to grow consistently and take advantage of the huge addressable market ahead of it.

However, there are also some significant risks.

I want to downplay the systematic risk and the business model/technology risk here, as the former applies to everybody, and the latter seems not to have been a serious problem for Pagaya.

However, the balance sheet risk is real, and it has materialized in the future. It’s currently impossible to measure the full extent of this risk as it’s a company playing with advanced financial instruments. It’s literally impossible for any outside investor to gain full visibility of operations. They are manipulating financial instruments, and you can’t know whether they are doing it all transparently. These are risks that you can’t mitigate by adjusting your discount rate.

What can you do?

You can reflect the risk in your position sizing.

You can limit your exposure with a small position. If the bull case plays out, you’ll be rewarded handsomely; if one of the lethal risks materializes, you won’t lose much.

How will I play it?

Well, I won’t use dry powder to buy Pagaya. I am already overexposed to financials, and I don’t want to grow this exposure further at this point. What we’ll do is move some of the money invested in financials to Pagaya. This will grow my diversification within the segment and reduce my exposure to company-specific risks while growing my surface area in the industry, better positioning the portfolio to take advantage of the possible bull case for the industry.

I hope this helps.