Claude for Credit Memos: Faster First Drafts, Same Judgment

1. The Credit Memo Is the Same Job Every Time

A credit memo has a shape, and it barely changes from deal to deal. Borrower overview, financial summary, the spread, leverage and coverage, the structure, the covenant package, risks and mitigants, a recommendation. Every memo your team writes follows that skeleton, in roughly the same order, pulling from analysis the team has already done.

That sameness is the tell. Anything with a fixed structure, written over and over from work that already exists, is assembly. Assembly is not the thinking. It is the packaging around the thinking, and packaging is exactly what a language model is good at.

Claude is Anthropic's AI assistant, strongest at long, dense documents and careful drafting. Point it at the memo and it does the part that eats analyst evenings: turning the spread and the diligence into a clean first draft in your firm's format. The underwriter still owns the credit. What changes is that they start from a draft instead of a blank page and a template.

This guide is about doing that well, not running a demo. The setup, the sections Claude drafts, the verification that keeps it honest, and the places it breaks if you let it.

2. The Data Rule Comes First

Before any of this, decide where the borrower data goes. That decision comes before the first prompt, not after the pilot has already leaked a file.

Borrower financials are confidential and usually under an NDA. So the rule is short: keep borrower material on Claude Team or Enterprise. Anthropic does not train its public models on business data from Team and Enterprise accounts. The consumer plans (Free, Pro) can use your inputs to improve models unless you opt out, which is the wrong footing for a credit file.

Notice what this is not. It is not a promise that nothing is stored. Team and Enterprise chats carry normal retention. The point is narrower, and it is enough: your borrower's numbers are not feeding a public model, and they sit inside an account your firm controls. The fuller security frame for a credit shop is in Claude for private credit.

Set the plan and the data rule once, write them down, and every analyst inherits the same boundary. This is the cheapest control you will ever put in place, and the one that saves the whole effort from a bad LP conversation later.

3. Build the Project Before You Draft

The difference between a party trick and a tool is setup. A cold chat gives you a generic memo. A Project gives you your memo.

A Project is a Claude workspace that holds standing instructions and reference files, so the same context applies to every chat inside it. Load three things. Your memo template, so the draft comes back in your section order and your house format. Your house language, the phrasing your committee expects for risk ratings, structure, and recommendation. And your credit policy: the box, meaning the leverage, coverage, sector, and structure parameters a deal has to fit, plus your definitions of EBITDA and your covenant conventions.

Now the draft is not a stranger guessing what a credit memo looks like. It drafts inside your standards, using your metric definitions, because you told it what they are. "Adjusted EBITDA" means the same thing in every memo the Project produces, and the add-backs follow your policy rather than the model's guess.

Do this once and every memo out of the Project starts from the same template and the same policy. That consistency is half the value. The other half is time. Where the Project sits in the wider tool landscape is covered in the best AI tools for private credit.

4. What Claude Drafts, Section by Section

Feed the Project the borrower file: the CIM, the financials, the diligence findings, the term sheet. Then it drafts the memo one section at a time, in your order.

Borrower and business overview. The company, the model, the market, the sponsor. Claude reads the CIM and writes the summary a committee member reads first.

Financial analysis and spreading summary. The revenue and EBITDA story, the margins, the leverage and coverage metrics, the trend across periods. It writes the narrative around the spread you have already built. The spreading and extraction work that feeds this is in AI credit underwriting.

Transaction and structure. The use of proceeds, the facility, the pricing, the security, and the position in the capital structure.

Covenant package. The financial covenants, the levels, the headroom against the base case, and the definitions that decide whether a level is ever tripped.

Risks and mitigants. The credit risks by category (business, financial, structural, management, market), each paired with its mitigant, drawn from the diligence rather than invented.

Recommendation. A drafted recommendation with the proposed terms, written for the underwriter to sharpen, press on, and own.

That is the whole memo in a first pass. Hours of drafting compressed into minutes of generation, so the analyst spends their time testing the risks instead of formatting the document. The same data-to-narrative pattern, seen across deal and portfolio memos, is laid out in the AI IC memo and board pack guide.

5. Every Figure Tied to Its Source

Here is the rule that makes the whole thing safe. Every number in the memo traces to a source you can point at.

A language model can produce a clean, confident, wrong number. It does not know the number is wrong, because it is drafting prose, not running a calculation. So you do not trust the figures in the draft. You check them. Leverage, coverage, the covenant headroom, every metric that drives the credit gets confirmed against the spread or the source document before the memo moves.

The practical version is a habit, not a lecture. Ask Claude to cite the source for each figure it uses. Reconcile the drafted numbers back to the model. Sign off before anything reaches committee. The memo is faster to produce, and the numbers are exactly as reliable as they were before, because a human still stands behind each one.

The cost of a wrong leverage figure in a credit decision is not a typo. It is a mispriced or misstructured loan. That asymmetry is the entire reason verification is not optional here, and it is why the discipline has to be built into the process rather than left to whoever is drafting at midnight.

6. The Judgment Does Not Move

Claude drafts the recommendation. It does not make it.

The credit decision, the risk rating, the structure, the pricing: those are judgments with asymmetric downside, and they belong to the underwriter and the credit committee. The model assembles the evidence and proposes words. A person decides whether the words are right.

This matters most in two places. The recommendation, which a credit professional has to believe and defend, not inherit from a draft. And the risk framing, where a model tends to state every risk in the same flat, even tone when the underwriter knows that one of them is the whole deal. The severity call, the emphasis, and the judgment about which mitigant actually holds are the human's to make.

When a regulator, an LP, or your own risk function asks why you made a loan, the answer has to be a documented human rationale. Never "the model recommended it." AI drafts and flags. A credit professional concludes and signs. That line is the whole governance model for credit, and it does not move.

7. Cowork Assembles the Full Pack

Drafting one section in a chat is the starting point. A full committee pack is more than one section.

Cowork is Claude's agentic working mode. Instead of answering a single prompt, it works through a multi-step task on its own. For a credit memo, that means taking the borrower file and assembling the whole draft: each section in order, the exhibits laid out, the covenant table built, the risks organized by category, all in your template.

The analyst's job shifts from writing to directing and checking. You point Cowork at the deal folder, it produces the assembled draft, and you review it section by section against the sources. The verification discipline from section five does not relax because an agent did the assembly. If anything it matters more, because more of the document was drafted in one pass, with fewer moments where a human eye crossed each number.

Used this way, the memo goes from a days-long build to a focused review. The judgment, again, is unchanged. The agent moves the paper; the credit professional still owns the credit.

8. Where It Breaks

Every honest tool guide includes the failure modes. Here are the ways a Claude-drafted credit memo goes wrong, and the single habit that catches each one.

None of these are reasons to sit AI out. They are reasons to use it with the discipline in this guide. A team that knows where a tool breaks gets far more out of it than one that believes the marketing and gets surprised in committee.

9. From One Memo to a Standing Capability

Most firms start with one analyst drafting one memo in a chat. That is the right way to start. It is not where the value settles.

The value compounds when memo drafting becomes a standing capability: the Project holds your template, house language, and credit box; it connects to where the borrower data and the spreads already live; and every underwriter on the desk drafts from the same setup. New analysts learn your format by working inside it, not through four revision cycles with a busy VP.

At that point the memo stops being a document one person wrestles the night before committee and becomes part of how the desk runs. The productized version, built into your process, is investment committee memo automation, fed by the borrower intelligence that reads the underlying material into a usable shape.

The broader arc for a credit shop, from a single workflow to a connected system, is in the complete guide to AI in private credit.

10. What Actually Changes

Strip away the noise and the change is narrow, and it is real.

The memo is faster to draft. A first pass that took an analyst a day or more comes back in a form worth editing: in your format, with the sections filled from the borrower file. That reclaimed time goes back to the work that deserves it, which is pressing on the risks, testing the structure, and sizing the credit.

What does not change is the judgment. The rating is still yours. The recommendation is still argued and owned by a person. Every figure is still verified. The credit committee still decides. A borrower does not get a better loan because the memo was drafted quickly, and a weak credit does not become sound because the write-up is clean.

That is the honest pitch. Not a machine that makes credit decisions. A tool that removes the assembly around the decision, so your best people spend their hours on the part that was always theirs.

11. Where to Start

Pick the plan and the data rule this week: Claude Team or Enterprise, borrower material on it and nowhere else. Then build one Project with your memo template, your house language, and your credit box.

Draft your next memo inside it. Feed it a real borrower file, let it produce the first pass, and verify every figure against the source before the memo moves. Do that across three or four live deals and you will know exactly what it saves and where it needs a human hand, from evidence rather than a vendor's promise. The credit memo automation work is the productized version once you are ready to build it into the desk.

If you want the setup done around your firm's format and policy rather than a generic template, that is what an AI Readiness Sprint produces: the plan, the data rule, the Project, and the first memo workflow proven on real deals in one to two weeks. Faster first drafts, the same credit judgment, held to your standard.