AI can do the gathering and reconciling a private credit screen runs on. It can't do the big judgment calls at either end, and shouldn't.
“How long until we have a view?”
That’s the question when a new name comes in. It’s in the email thread with the origination desk, on the credit committee calendar, in the conversation the head of credit has later this afternoon.
One credit team described it to us as the better part of a week before they’re in a position to decide whether to advance a deal to diligence. It doesn’t take an analyst that long to form their risk assessment. So what, exactly, is the bottleneck in private credit screens?
Look at where the time goes on the path to forming a view. The analyst needs to locate and reconcile the data room and work out how the borrower's structure actually fits together before any read can start. Additional documents arrive in inconsistent formats. Naming conventions are different between borrowers and again between what the originator sent over and what the company filed. No two borrowers disclose the same set of things or put them in the same place. When an analyst opens a folder, they first need to answer the question of where the information even sits before they can figure out what it tells them about the credit. Repeat over and over, document after document.
Teams consistently report to us that roughly 80% of the time it takes to form their assessment is taken up by collecting and reconciling, not evaluating the credit. That 80% is the work that can move to AI.
“Move” is the operative word, because this isn’t about helping the analyst gather and reconcile faster. Yet that’s how analysts are using AI: assisting in surfacing documents, flagging matches, speeding up search. But the analyst is still driving the screen’s assembly, they’re just doing it faster now. An agent can do this work and hand back to the analyst the assembled work. AI assistance compresses execution time. An agent reassigns the execution work altogether.
The execution work agents own in a credit screen is bracketed between two acts of human judgment.
The first human act is framing the screen. Before any gathering starts, an analyst needs to establish what the screen must answer: what matters with this borrower, what the credit box requires, what’s in scope. Drawing on the firm’s thesis and criteria, the analyst shapes what the agent will do when executing the screen.
The second human act is reviewing and forming a preliminary view on the deal. The agent hands them a fully assembled and structured screen, and they review the data and sources, form an opinion, and add it to the screening output. When an analyst forms a view during the manual execution of the screen, their view is still limited by what they were able to get done in time. When an agent owns execution, the analyst’s evaluation is no longer a rushed effort against what could be assembled before the clock ran out. It's a deliberate read on the full picture.
Assembling a screen takes small judgments of its own. Which of two figures is authoritative. Whether a subsidiary sits inside the credit group. How to structure a picture the documents don't. The agent makes these calls as it works, according to the firm's method. They are visible and correctable parts of execution, and the analyst has the time to check them at review. What the agent never makes is the call the screen exists to support: whether this credit is worth the firm's time and capital.
Review only saves time if the analyst can trust the output without having to rebuild it. A defensible screen needs to carry its provenance. Every figure traces to the document it came from. Every reconciliation shows which source it used and why. The analyst checks the trail rather than attempting to re-derive the picture they have in front of them.
Sandwiched in between these two human acts, the agent goes to work on the framed screen. It gathers, reconciles, structures, and drafts the screen. This is the execution layer of a credit screen: the work between raw signal and an output an analyst can review and edit. The agent is bounded above by the analyst's frame and the firm’s requirements, and below by the raw inputs.
The finalized screen goes to the deal lead or head of credit or whoever decides whether to advance the deal to diligence.
There's a real objection to this approach worth addressing. Digging through a messy data room teaches you something. A borrower whose disclosures are chaotic, whose numbers conflict, whose structure takes a day to map, is telling you how the business is run. An analyst doing the digging carries that. One that’s handed a clean output might not.
Some of what the digging teaches is real signal, but opening the 40th file to find where the right EBITDA figure sits doesn’t. The answer is to surface the exceptions. An agent that flags conflicting numbers, opaque structures, and thinner-than-peer disclosure gives the analyst signal without the manual retrieval work. These are all part of the agent’s output and the analyst’s review.
As the firm’s book grows, the execution burden grows with it. This is where capacity pressure appears first, not in the analyst’s ability to effectively evaluate more credits, but in the hours available for them to execute the screens needed to evaluate them.
When execution demands outpace the team, the casualty isn’t always deal volume, it’s maintaining the same standard across every deal they look at. Some names get the full picture assembled and evaluated. Others get what time allowed. This kind of inconsistency isn’t visible in the output; analysts produce consistent-looking outputs and every screen looks like a screen.
In a market environment that’s becoming increasingly skeptical of the growth-plus-big-logo-equals-safe-credit assumption, firms have good reason to care whether disciplined selection is actually happening for every name. This is a different question than whether the team is fast, or getting faster with the assistance of AI. Moving the execution work to agents allows the standard to hold across a growing book.
What stays human
Framing a screen is human. Forming a view is human. Decisions to advance a deal or allocate capital are human ones. The manual gathering and reconciling work required for humans to make good, informed decisions doesn't have to be, and shouldn’t be. Agents can do this work, and should be.
The judgment at both ends of the workflow stays human and gets better because the execution work in the middle doesn’t have to.