A commercial credit memo takes an analyst four to eight hours, and most of that is not writing. It is retyping tax returns and financial statements into a spreadsheet, recomputing ratios, and hunting for the page a number came from. LenderAnalyzer does that half. Upload the borrower's returns, statements and bank activity, and get a spread, the ratios, global cash flow and a source citation behind every figure, ready to drop into the memo template your committee already uses. Self-serve from $99 a month, no implementation project.
Upload a document to extract
Drop files here or click to upload
Up to 50 files
Uploading...
Upload a bank statement and watch the analysis run live, free, no signup required.
The credit memo is the document a commercial loan lives or dies by, and it is also the place where a credit department quietly loses most of its week. Published estimates from lenders and vendors alike put a full commercial write-up somewhere between four and eight hours. Ask an analyst where those hours went and almost none of the answer is analysis. It is keying three years of tax returns into a spread template, rebuilding the debt schedule, recomputing coverage after the officer changes the structure, and then chasing back through a 60 page PDF to find the page that supports a number a reviewer questioned.
LenderAnalyzer automates the mechanical half. It reads the borrower's business and personal returns, the interim financials, the debt schedule and the bank statements, produces a normalized spread with the ratios your credit policy calls for, computes debt service coverage and global cash flow across the operating entities and the guarantors, and keeps every extracted figure linked to the page and line it came from. What lands in your memo template is a set of numbers that a second reviewer, or a regulator, can trace without asking you anything.
Where we stop is deliberate, and it is worth being plain about it. LenderAnalyzer does not write your risk narrative. It will not invent the mitigants, judge whether a customer concentration is survivable, or decide that a policy exception is worth taking. Several vendors will draft that prose for you, and in the comparison below we say so and say where they are the better fit. Our position is that the narrative is the part of the memo a credit officer is paid for, and the data assembly is the part that should have stopped being manual years ago.
The memo does not get shorter. It gets assembled from data that is already structured, already reconciled and already cited, which changes both how long it takes and how well it holds up in an exam.
Every ratio in a credit memo is a function of the spread. Debt service coverage, leverage, current ratio, working capital, the trend commentary, the risk rating that falls out of the model: all of it is arithmetic performed on numbers that a human typed in from a PDF. One transposed figure in the depreciation line moves EBITDA, which moves coverage, which moves the rating, which moves the recommendation, and nothing in a Word document flags that it happened. Automating extraction does not just save the keying time. It removes an entire class of error that is invisible until loan review finds it eighteen months later.
The question that costs a credit department the most time is not "what is the number". It is "where did this number come from". A reviewer, a committee member, a loan review officer or an examiner asks it about a handful of figures on every deal, and answering it means reopening the source PDF and finding the line. When each extracted value stays linked to the page it was read from, that question is answered by clicking it. This matters more than it sounds like it should: it is the difference between a memo that can be verified in minutes and one that has to be partly rebuilt to be verified at all.
Two analysts spreading the same borrower will produce two different EBITDA figures, because add-backs are a judgment call and every credit department has an unwritten version of the policy. That inconsistency is fine on one deal and a finding across a portfolio, because the risk ratings are no longer comparable and the concentration reporting built on top of them is not either. Running the extraction and the normalization through one configured template means the same tax return line lands in the same spread row on every file, and any deviation is a deliberate analyst override rather than an accident of who was assigned the deal.
New money gets the attention, but most commercial credit departments spend more hours on annual reviews and renewals than on new originations, and a renewal is the most mechanical memo there is. The structure is known, the borrower is known, and the work is updating the spread with one more year of financials and explaining what changed. That is close to a pure data task, and it is the first place credit memo automation pays for itself. A department that can turn a renewal package around in an afternoon instead of a day and a half stops carrying the annual review backlog that shows up in every exam.
What each approach delivers, how long it takes, and who it suits. Last updated August 2026.
Swipe sideways to see the full comparison
| Approach | What it produces | Time per memo | Typical cost |
|---|---|---|---|
| LenderAnalyzer This page | The data half: normalized spreads from tax returns and financials, ratios, DSCR, global cash flow and bank statement analysis, every figure cited to its source page and exported into your existing memo template. You write the narrative | Assembly in under an hour, then your write-up | Published, $99 to $399/mo |
| Analyst in Excel and Word | The complete memo at full judgment quality, in whatever format the committee prefers. Where it wins: nothing understands a messy borrower better than an experienced analyst. Where it hurts: four to eight hours a deal, and two analysts will not spread the same file the same way | Four to eight hours | Fully loaded analyst time |
| AI credit memo generators (GLIB.ai, Aloan, Crediflow type) | A full drafted memo including the risk narrative, which is genuinely more than we produce. Where they win: if your goal is a finished document rather than a finished analysis, this is the category to buy. The tradeoff is that a generated narrative still has to be read line by line before it goes to committee | Minutes to draft, plus review | Quote-based, sales-led |
| Memo module inside the LOS (nCino, Abrigo type) | The memo inside the system of record, with routing, approvals, version history and the audit trail attached. Where they win: workflow and governance in one platform, which a bank past a certain size needs. The tradeoff is an implementation project measured in months and a licence to match | Depends on the workflow, not the tool | Enterprise licence plus implementation |
Comparison compiled by LenderAnalyzer from public vendor materials; see the date noted above each table. Competitor names are trademarks of their respective owners; figures may change, so verify current details with each vendor.
Computed deterministically from every extracted transaction, every figure traceable to its source line.
Computed across the full statement period, carried forward day by day.
Deposits vs withdrawals and net flow, broken down month by month.
Every insufficient-funds and overdraft incident counted, with fees totaled.
Recurring deposits grouped into income streams with estimated monthly amounts.
Debits to other lenders and funders detected and totaled per month.
Days below zero across the period, a direct stress signal.
The biggest credits with dates and sources, concentration flagged.
Automatic red and yellow flags your analysts can review in seconds.
Drop in PDFs, scans or photos, one statement or a multi-month package, from any bank.
Every transaction is extracted, then cash flow, balances, income streams, NSF activity and debt payments are computed.
Read the underwriting snapshot, download the Excel report, or pull structured JSON into your LOS via API.
28 lending document types extracted out of the box, build the complete picture of an applicant's financial situation.
Common questions from lending and credit teams.
A credit memo, also called a credit write-up or credit approval memorandum, is the written case for approving or declining a commercial loan. It sets out who the borrower is, what they are asking for, how the facility is structured, where repayment comes from, what the financial analysis shows, what could go wrong, and what the officer recommends. It is the document the credit committee votes on and the document an examiner reads first when they pull a loan file.
At minimum: an executive summary with the recommendation, the borrower and guarantor profile, the credit request and facility structure, the purpose and the primary and secondary repayment sources, financial analysis with the ratios your policy requires, global cash flow where there are related entities or guarantors, collateral description and loan to value, the proposed covenants, the identified risks with their mitigants, the assigned risk rating, and a statement of compliance with credit policy including any exceptions.
Four to eight hours is the usual range for a full commercial write-up, and longer for a complex multi-entity or multi-facility deal. Renewals and annual reviews are faster, often two to four hours, because the structure is already known. The majority of that time is not writing. It is spreading the financial statements, rebuilding the debt schedule, recomputing ratios and locating the source pages behind the numbers.
AI can draft one, and several vendors sell exactly that. What it cannot do is take responsibility for it. A generated memo still needs a credit officer to check that every figure ties to a source document, that the risk narrative reflects the actual deal rather than a plausible-sounding pattern, and that the recommendation is one the officer will defend to a committee and an examiner. The safest use of automation today is the data layer, where the output is verifiable, rather than the judgment layer, where it is not.
The credit analysis is the work: spreading the financials, computing the ratios, testing repayment capacity, sizing the collateral, stress testing the structure. The credit memo is the document that presents that work and asks for a decision. The analysis can be right and the memo still fail, usually because the risks were listed without mitigants or the recommendation did not follow from the numbers presented.
It depends on the size of the institution. At a community bank the relationship manager or commercial lender often writes it with support from a credit analyst. At a larger bank the credit analyst writes the analysis and the memo, and the relationship manager owns the recommendation and defends it in committee. In both models credit administration reviews the memo for policy compliance before it reaches the approval authority.
No, and a vendor claiming otherwise is selling you a compliance problem. What automation replaces is data entry: keying returns into a spread template, recomputing ratios after a structure change, and paging through PDFs to find the support behind a number. The analyst still decides what the numbers mean, whether the mitigants are real, and what the risk rating should be. Those are the parts an examiner will hold a named person accountable for.
The enterprise tools in this category are quote-based and sales-led, and pricing is usually a function of loan volume, seats or documents, with an implementation project attached. Platform modules inside a loan origination system are licensed annually and priced per user. LenderAnalyzer publishes its pricing and starts at $99 a month self-serve, so a two-person credit team can put a real deal through it before anyone signs anything.
How credit teams run these calculations by hand, so you can see exactly what the software automates.
The full section-by-section structure, with the ratios each part needs.
Where generated narrative helps, and the two places it should not go.
The mechanical step that consumes most of the memo hours.
Combining entity and guarantor cash flow for the coverage section.
What the memo has to support before a rating can be defended.
The renewal memo, where automation pays back fastest.
Analyze your first statements free, plans from $99/month, 50% off billed annually.
