I keep seeing the same pattern in credit.
Things look calm for years. Low rates. Easy money. Few defaults. Then a couple “weird” events hit at the same time and everyone remembers what risk looks like.
That is where US private credit is right now.
What This Course Covers (And Why It Matters)
Private credit grew up in the post-2008 world. Banks pulled back from certain types of lending due to regulation. Private lenders stepped in. The market grew roughly fivefold since 2008.
Now we have a new environment:
- Higher rates are pressuring borrowers
- Some losses are showing up in ugly ways
- Retail-friendly fund structures are being tested
- AI is forcing a rethink of “safe” borrower assumptions especially in software
This module is an investigation into four narratives that look separate on the surface but connect when you follow the cash:
- Fraud and underwriting failures (Tricolor and First Brands)
- AI-driven disruption risk in software and tech borrowers
- Semi-liquid redemption gates (Blue Owl OBDC II as the case study)
- Structural vulnerabilities like payment-in-kind and valuation opacity
The real question I’m trying to answer is simple:
Are these isolated episodes or early signs of a broader credit cycle turning?
Quick Market Context: Private Credit Is Huge And Not Fully Cycle-Tested
A few facts that frame the whole conversation:
- The US private credit market is roughly $2–$3T
- It expanded in a decade where:
- Interest rates were low
- Capital was abundant
- Defaults were limited
- At today’s scale it has not been tested through a full credit cycle
Two other numbers from the lesson that jumped out at me:
- 15%+ of borrowers are reportedly struggling to cover current interest payments
- US banks have about $1.7T of lending to non-bank lenders (meaning stress can leak back into the banking system)
Private credit is not “off in the corner.” It is intertwined.
Risk Narrative #1: Fraud Was The First Real Wake-Up Call
The first cracks that got broad attention were tied to alleged fraud and opaque financing.
Tricolor Holdings (subprime auto lender)
- Collapsed and filed Chapter 7 after allegations tied to double-pledging vehicles as collateral
- “AAA” rated securities dropped hard (down to around $0.12 on the dollar in the module discussion)
- Multiple large institutions had exposure
The Jamie Dimon framing from the module is the right mental model:
“When you see one cockroach there are probably more.”
First Brands (auto parts roll-up)
- Collapsed with $6B+ in private debt
- Concerns included opaque off-balance sheet financing
- Loans that were previously marked near full value later traded around one-third of par (roughly $0.30-ish levels)
Why this matters even if you think it’s “idiosyncratic”
The consensus defense is:
- These were fraud-driven cases
- Asset-based lending issues
- Not representative of sponsor-backed direct lending
Maybe. But the damage is still real:
- It dents trust
- It raises questions about underwriting and monitoring
- It stresses valuations in a market that does not mark-to-market cleanly
Risk Narrative #2: AI Disruption Is A Credit Problem Now Not Just An Equity Story
This part is easy to miss if you only follow stock prices.
Private credit lenders have loved enterprise software since around 2020 because the classic SaaS pitch sounds perfect for lenders:
- Recurring revenue
- High margins
- Sticky customers
- Predictable cash flows
Those characteristics support big unitranche loans.
The thesis is getting challenged by AI in a very direct way:
- AI agents
- Coding tools
- Workflow automation
- Pressure on seat-based licensing models
If the “sticky” revenue gets less sticky the credit math changes.
UBS framing from the module
The module highlights UBS work that basically says:
- 25%–35% of some portfolios could be exposed to AI disruption risk
- In an aggressive scenario UBS models meaningful default pressure tied to software disruption
A related signal: the market has been repricing private-credit-linked managers harder than the broad index.
In the lesson I point out how the S&P was basically flat in a window where names like:
- Ares
- KKR
- Blue Owl
- TPG
were down much more.
That pricing gap matters because credit is often slower to reprice than equities. When equities re-rate quickly it is a warning that credit assumptions may be stale.
Risk Narrative #3: Blue Owl OBDC II And The Semi-Liquid Redemption Gate
This is the example that made the structure risk feel real for a lot of people.
The product design problem
Private credit loans are illiquid. You cannot just sell them like ETFs.
But the industry has packaged illiquid loans into semi-liquid vehicles marketed through retail and wealth channels that offer:
- Quarterly repurchases/redemptions
- The impression of liquidity
- But only up to limits
When stress hits and too many investors ask for cash at once the fund can impose a gate.
That is what happened in the Blue Owl OBDC II case discussed in the module.
What a gate actually means
A gate is basically the manager saying:
- We can’t meet all redemptions without dumping assets
- So we limit withdrawals (often a % of NAV per quarter)
- Investors have to wait
If you’ve seen The Big Short you’ve seen the “closing the gate” dynamic play out in narrative form. Different asset class. Same investor psychology.
Why activists show up
When a fund gates redemptions, activists can:
- Question the stated NAV
- Offer tender deals at discounts (say $0.70 on the dollar)
- Put pressure on the manager to prove valuations are real
In the module I note the key point:
- Blue Owl was able to sell loans near par and return capital
- This looked more like a liquidity event than a solvency event
That distinction is critical.
But the existence of the gate is still a stress test result. It tells you where the structure can break under pressure.
Risk Narrative #4: Quiet Structural Vulnerabilities (PIK, Valuations, And Bank Links)
The most dangerous risks in private credit are often the boring ones.
Payment-in-kind (PIK) is rising
PIK means interest can be paid with more debt instead of cash.
In the module:
- PIK features climbed from about 7.4% of deals (2021) to 11%+ (2025)
PIK can be fine when it is strategic. It is a problem when it is reactive.
Reactive PIK is basically:
- “Borrower can’t pay cash today”
- “So let’s pretend it’s fine and add it to the balance”
That defers pain into the future and can amplify losses later.
Valuation opacity is built in
Many private loans:
- Do not trade frequently
- Are not marked-to-market the same way public bonds are
- Can be held at values that look stable right up until they don’t
That creates room for:
- Delayed recognition of deterioration
- Disagreement between reported NAV and “real” clearing levels
Interconnectedness with banks
Banks have substantial lending exposure to non-bank lenders.
In the lesson the number is roughly:
- $1.7T of bank lending to non-depository financial institutions
- Around 13% of all bank loans
So stress in private credit can boomerang back into the regulated system.
What You’ll Learn In The Module (Learning Objectives)
This lesson is designed to help you build a clean mental model and a professional checklist. Specifically you’ll be able to:
- Identify key risk factors pressuring private credit:
- Fraud exposure
- AI disruption
- Liquidity mismatch
- Valuation opacity
- Explain Blue Owl OBDC II and why semi-liquid structures can fail under stress
- Evaluate UBS’s AI disruption framing and how sector concentration in software/tech can show up in credit risk
- Separate idiosyncratic events from systemic indicators so you can stay balanced and not panic on headlines
So Is Private Credit “In Trouble”?
My conclusion in the module is not “private credit is blowing up.”
It is:
- Private credit is not currently in crisis
- But it is moving into a more discriminating phase after years of easy growth
- The stress tests are arriving simultaneously
- And the market has not faced them at this scale before
The question is no longer whether there will be episodes.
There will be.
The question is whether they stay isolated or start to compound into something cyclical.
Key Takeaways
- The $2–$3T private credit market is being stress-tested in real time after a long easy-growth period.
- Fraud and opaque financing (Tricolor, First Brands) cracked confidence and forced ugly price discovery.
- AI disruption is now a credit issue especially for software-heavy portfolios built on SaaS cash flow assumptions.
- Blue Owl OBDC II highlights the structural risk in semi-liquid funds that promise periodic liquidity while holding illiquid loans.
- Rising PIK usage, valuation opacity, and bank interconnectedness are the quieter risks that can turn isolated problems into broader stress.
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