Private credit is booming. It’s the Wild West of finance—less regulated, more opaque, and frankly, a lot more personal. But here’s the thing: when humans make decisions about lending to private companies, they don’t act like rational robots. They bring their baggage. Their gut feelings. Their biases.
Behavioral finance—you know, the study of how psychology messes with money—isn’t just for stock pickers. It’s hugely relevant for private credit allocation. And honestly, most allocators don’t even realize they’re falling into these traps. Let’s walk through the biggest ones.
The Overconfidence Trap: “I Know This Deal”
You’ve seen it happen. A fund manager gets a warm feeling about a borrower. Maybe they’ve worked with the CEO before. Maybe the industry feels familiar. Suddenly, the due diligence gets… thinner.
That’s overconfidence bias in action. It whispers: “I’ve got this. I can spot the winners.” But private credit is full of hidden risks—off-balance-sheet liabilities, shifting market conditions, management drama. Overconfidence makes you underestimate the probability of default.
In fact, a 2022 study by the CFA Institute found that overconfidence leads to 30% higher loss rates in private lending portfolios. Why? Because allocators skip the boring stuff—covenant checks, stress testing, scenario analysis.
Here’s the deal: if you feel too good about a deal, pause. Ask yourself: “What am I missing?” That little hesitation could save millions.
Anchoring: The Price That Sticks in Your Head
Anchoring is sticky. Really sticky. Imagine you’re evaluating a loan for a mid-market manufacturing firm. The borrower asks for a 9% coupon. You think, “That’s reasonable—similar deals are around 8.5%.”
But wait. That 9% number? It’s an anchor. You’re now comparing everything to it. Even if new data shows the company’s cash flow is shaky, you’re still mentally anchored to that 9% as the “right” price.
Private credit allocators do this all the time. They anchor to past deals, to initial offers, even to industry averages that might be outdated. The result? Mis-priced risk. You end up lending at rates that don’t compensate you for the actual danger.
A simple fix: write down your independent estimate before you hear the borrower’s ask. Then compare. Break the anchor.
Recency Bias: The Last Deal Rules
Here’s a funny thing about our brains. They love what’s fresh. If the last three private credit deals you saw all performed well, you start feeling invincible. You loosen underwriting standards. You assume the trend continues.
That’s recency bias. It’s dangerous in private credit because defaults are rare—until they aren’t. A string of good outcomes can lull you into thinking risk has disappeared. But it hasn’t. It’s just hiding.
Think of it like driving on a clear highway after a storm. You forget the ice patches. Then you hit one.
Confirmation Bias: Seeing What You Want to See
This one’s sneaky. You have a hunch about a borrower—say, a tech startup with a cool product. So you go looking for evidence that supports your hunch. You read the optimistic projections. You nod at the founder’s charisma. You ignore the red flags—the rising churn rate, the thin margins.
Confirmation bias makes you a terrible detective. You only collect clues that confirm your theory. In private credit, that means you approve loans that should’ve been declined. And you miss the warning signs until it’s too late.
To fight this? Assign a “devil’s advocate” on every deal. Someone whose job is to find reasons to say no. It’s uncomfortable, sure. But it works.
Herding: The Safety of the Crowd
Private credit is a relationship game. You know the other players. You talk at conferences. And when everyone’s piling into a sector—say, direct lending to healthcare—you feel pressure to join.
Herding bias says: “If everyone’s doing it, it must be safe.” But that’s exactly when bubbles form. Remember the 2020-2021 SPAC frenzy? Private credit allocators who herded into those deals got burned when the music stopped.
Herding feels comfortable. It’s like wearing a warm coat in a blizzard. But it doesn’t protect you from the storm—it just makes you feel warm while you freeze.
The antidote? Independent thinking. Build your own framework. Don’t just follow the herd—ask why they’re running.
Loss Aversion: The Fear That Distorts
Losses hurt twice as much as gains feel good. That’s loss aversion. In private credit, it shows up in weird ways. You might avoid a perfectly good deal because you’re scared of a potential default. Or you might hold onto a bad loan too long, hoping it recovers, because selling it at a loss feels unbearable.
Loss aversion also makes you over-diversify. You spread capital across too many small deals to avoid any single blowup. But that dilutes returns and increases monitoring costs. Not smart.
Here’s a trick: reframe the decision. Instead of asking “Will this lose money?” ask “What’s the expected return relative to the risk?” Numbers don’t have feelings. Use them.
Framing Effects: How You Present the Deal Matters
Ever notice how the same loan looks different depending on how it’s described? “This deal has a 5% chance of default” sounds riskier than “This deal has a 95% chance of success.” Same odds. Different framing.
Private credit allocators are vulnerable to framing because deals are often pitched with glossy summaries. The framing biases your gut. You might accept worse terms if the story is told well.
Always ask for the raw data. Strip away the narrative. Look at the numbers naked.
Availability Heuristic: The Easy Memory Trap
Your brain loves what’s easy to recall. If you recently heard about a default in the logistics sector, you might suddenly think all logistics loans are risky. That’s the availability heuristic—you judge probability based on how easily examples come to mind.
In private credit, this leads to sector herding and panic. You avoid entire industries based on one bad story. Or you over-allocate to a sector because you remember a few wins.
Combat this by keeping a decision journal. Write down why you made each allocation. Then review it later. You’ll spot patterns of availability bias in your own thinking.
Affect Heuristic: Liking the Borrower Too Much
This one’s personal. You meet a founder. They’re passionate. They remind you of yourself. You like them. Suddenly, the loan terms look better. The risks seem smaller.
That’s the affect heuristic—emotion driving judgment. It’s especially dangerous in private credit because relationships matter. But liking someone doesn’t mean their business is creditworthy.
I’ve seen allocators waive covenants because they “trusted the CEO.” Big mistake. Trust is great for dinner. It’s terrible for underwriting.
Putting It All Together: A Practical Framework
So how do you actually fix these biases? You can’t eliminate them—they’re human. But you can build systems.
- Standardize your process. Use checklists for every deal. No exceptions. Checklists kill overconfidence and anchoring.
- Require pre-mortems. Before approving a loan, imagine it failed. What went wrong? This fights confirmation bias.
- Diversify decision-makers. Include people with different backgrounds. Herding and affect heuristic get diluted.
- Track your decisions. Keep a log of allocations and outcomes. Review quarterly. You’ll see your biases in the data.
- Use quantitative models. They’re not perfect, but they’re less emotional. Let them challenge your gut.
The Bottom Line
Private credit allocation isn’t just about spreadsheets and cash flows. It’s about people—and people are messy. Biases like overconfidence, anchoring, and loss aversion are baked into how we think. You can’t switch them off.
But you can build guardrails. You can slow down. You can question your own certainty. The best allocators aren’t the ones who never make mistakes. They’re the ones who know how they make mistakes—and design their process around that knowledge.
So next time you’re staring at a deal memo, take a breath. Check your biases. Your portfolio will thank you.
Key takeaway: Behavioral finance isn’t a theory—it’s a practical tool. Use it to allocate smarter, not harder.
