credit-memo 📝

Generate IC credit memos from structured deal inputs.

Takes borrower profile, loan terms, financial data, impact metrics, and risk factors as structured Python inputs and generates a formatted Investment Committee credit memo in Markdown or Word (.docx) format.

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Why credit-memo?

Every CDFI analyst, IC committee, and private credit team writes credit memos from scratch in Word. credit-memo standardizes the process — define your deal inputs once, generate a professional IC memo instantly.

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Installation

pip install credit-memo

# For Word .docx output
pip install credit-memo[docx]

credit-memo imports nothing outside the standard library. Only the optional [docx] extra adds a dependency (python-docx).

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Quickstart

from creditmemo import (
    CreditMemo, DealProfile, BorrowerProfile,
    LoanTerms, FinancialData, ImpactData, RiskFactor,
)

borrower = BorrowerProfile(
    name="Southside Community Health Center",
    borrower_type="nonprofit",
    sector="healthcare",
    state="IL",
    city="Chicago",
    year_founded=2005,
    ceo_name="Dr. Maria Johnson",
    mission="To provide quality healthcare to underserved communities.",
    is_cdfi_certified=False,
)

loan = LoanTerms(
    deal_type="loan",
    amount=2_500_000,
    interest_rate=0.045,
    term_years=10,
    amortization_years=20,
    io_periods=12,
    collateral="First mortgage on real property",
    use_of_proceeds="Acquisition and renovation of community health facility",
    min_dscr_covenant=1.20,
)

financials = FinancialData(
    revenue_y1=2_800_000, revenue_y2=3_000_000, revenue_y3=3_200_000,
    net_income_y1=150_000, net_income_y2=180_000, net_income_y3=210_000,
    dscr=1.35, current_ratio=1.8,
)

impact = ImpactData(
    jobs_created=18, jobs_retained=32,
    patients_served=8500,
    is_low_income_area=True,
    is_nmtc_eligible=True,
    is_minority_borrower=True,
)

deal = DealProfile(
    deal_name="Southside Health Center — $2.5MM Term Loan",
    borrower=borrower,
    loan_terms=loan,
    financial_data=financials,
    impact_data=impact,
    recommendation="approve_conditions",
    prepared_by="Jay Patel",
    prepared_date="2026-05-06",
    fund_name="NCIF Community Lending Fund",
    conditions=[
        "Receipt of final appraisal satisfactory to lender",
        "Evidence of $500k matching funds from borrower",
    ],
)

memo = CreditMemo(deal)
print(memo.to_markdown())
memo.save_markdown("southside_health_memo.md")
memo.save_docx("southside_health_memo.docx")   # requires pip install credit-memo[docx]

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Word (.docx) Output

save_docx() writes headings, paragraphs, bulleted lists, section rules and every table in the memo as a real Word table — deal summary, proposed terms, NMTC structure, historical financials, balance sheet summary, credit metrics, projections, impact metrics, high risk factors, medium risk factors, low risk factors and the IC signature block: twelve in a memo with all of them populated. Risk factors are one table per severity, so a memo carrying only High risks renders ten. Tables use the built-in Table Grid style with a bold header row, and the rules between sections are paragraph borders rather than rows of underscores.

Numbered lists keep their numbers as text. Conditions of Approval and any ordered list you write into a text field arrive as ordinary paragraphs whose text still begins with 1., 2., 3. — not as Word list items. This is deliberate. Word does not restart a numbered list on its own, so styling them made the Conditions of Approval in a memo that also had an ordered list earlier print as 3, 4, 5. A number in this memo is a value an underwriter wrote; the package will lose a list's indentation before it will let Word choose a different number. Unordered lists do use Word's List Bullet style, because a bullet glyph says exactly what the - in the Markdown said.

save_docx() refuses text containing control characters — a vertical tab or form feed, which is what a paste out of a PDF often leaves behind — and names the character and the memo line in the error. They are not valid in a .docx and nothing is silently stripped. save_markdown() accepts them.

The .docx is a pure function of the Markdown the same deal produces: every heading, paragraph, list item, rule and table in the Word file comes from a line of that Markdown, and nothing carrying text is added that has no line behind it. Empty paragraphs are added: one after each table, as the spacer Word needs to keep a table off the next heading, and one per section rule. On the quickstart deal above that is 6 tables and 13 empty paragraphs — 7 rules and 6 spacers. The qualifier used to be missing here and present in render's own docstring, which is the direction that matters least and reads worst. It does not apply column widths, merged cells, number alignment, or a firm template.

credit-memo 0.2.0 and 0.1.0 printed the memo's front matter twice in every Word file — the title, the deal name and the whole Fund / Prepared By / Date / IC Date block appeared once as a hand-built cover block and again from the Markdown, in a different shape. 0.1.0 additionally dropped every table. If you generated Word memos with either release, regenerate them. See the changelog.

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How Dollar Figures Are Written

A figure is written in the $MM unit only where that unit is precise enough to describe it. Two decimals of $MM resolve to $10,000, so the crossover is $1,000,000 — the point where $10,000 is one percent of the figure. At or above it you get $2.50MM; below it you get exact dollars and cents, $4,999 or $4,999.60, with the cents suppressed when they are zero. A supplied zero is $0. Negative figures lead with the sign: -$4,000, -$100.00MM.

Below half a cent there is no honest cent figure to print, and rounding to $0 would put a non-zero figure behind the string a stated zero uses — the defect this section exists to describe. So a sub-cent magnitude is written as a bound rather than a value: <$0.01, or >-$0.01 below zero. Each is a true inequality about the number, and it keeps three things apart that would otherwise read the same:

| Net Income | $0 | <$0.01 | >-$0.01 |
| Origination Fee | 0.00% (<$0.01) |

A stated zero, a positive sub-cent figure and a negative one are three different strings. Those are all the forms a single figure takes: $0, <$0.01, >-$0.01, the cents form, the $MM form, and N/A for a figure you did not supply. The loan amount is the only place two of them appear together — see below.

This also means one table can mix the two units — | Revenue | $900,000 | above | EBITDA | $1.10MM |. That is deliberate. Through 0.2.0 the units were kept consistent by dividing everything by a million at two decimals, which meant every figure below $5,000 printed as $0.00MM — the same characters a stated zero prints. A $4,999 cash balance and a zero cash balance reached the Investment Committee as one string. The borrower snapshot was worse: one decimal, so total_assets=49_000 printed $0.0MM. If you generated memos for microenterprise or small-business deals with 0.1.0 or 0.2.0, the small figures in them are wrong — regenerate them. 0.2.1 is the release that fixes this.

The loan amount is the one figure written twice: $2,500,000 ($2.50MM), or just $250,000 below the crossover, where the parenthesised form would only be a coarser copy of the number beside it.

Two known costs of writing figures in the unit that fits them

A table can switch units inside the comparison it exists for. Every cell below is true, and the switch lands between the two figures a reader is meant to compare:

| Total Assets        | $999,999 |
| Total Liabilities   | $1.00MM  |
| Net Assets / Equity | -$1      |

| Revenue | $999,999 | $1.00MM | $1.00MM |

The second is the same thing inside one metric's own time series. The planned direction for 0.3.0 is unit consistency within a table: if any figure in a table falls below the crossover, the whole table renders in dollars. The dollars form is exact at every magnitude, so that buys consistency by rendering the large figures more precisely — never by collapsing a small one, which is what 0.2.0 did.

A change smaller than the rendered unit's granularity is invisible in the table and still visible to the revenue trend. Above the crossover:

revenue_y1=1_000_000, revenue_y3=1_004_999

| Revenue | $1.00MM | N/A | $1.00MM |
**Revenue Trend:** Increasing — revenue has been increasing over the
historical period.

Both cells are honest roundings of their inputs, and the trend is computed on the raw values you supplied, so nothing here is wrong — the table is coarser than the comparison. This is inherent to rounding at any precision and is not fixed by moving the crossover: at exact cents the same pair would be a fraction of a cent apart. The trend is computed on raw values on purpose; computing it on the rendered figures would make the memo's one analytical claim a function of the formatter and would report "stable" for a real change.

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Memo Sections Generated

1. Executive Summary — deal overview, recommendation, key terms table
2. Borrower Profile — organization description, mission, certifications
3. Transaction Structure — loan terms, collateral, covenants, NMTC structure
4. Financial Analysis — historical financials, key ratios, projections
5. Impact Analysis — jobs, units, demographics, eligibility flags
6. Risk Assessment — risk factors by severity with mitigants
7. IC Recommendation — formal recommendation with conditions and signature block

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Stating What You Know, and What You Don't

The eligibility and certification flags are three-state:

value	rendering
True	the affirmative line — ✅ Low-Income Area
False	an explicit negative — ❌ Not a Low-Income Area
None (default)	omitted entirely

is_cdfi_certified, is_mdi, is_low_income_area, is_nmtc_eligible, is_opportunity_zone, is_minority_borrower and is_women_borrower all work this way. Passing False says "we checked, and the answer is no"; leaving the field alone says nothing at all. Before 0.2.1 these were plain booleans defaulting to False, so the two were the same value and both rendered as silence.

The same principle applies to figures. Every Optional field is consulted with is not None — never for truthiness — so a supplied 0 is rendered as the number the caller stated: no cash on hand as $0, a 0% interest_rate — a forgivable loan, an EQ2 note, a QLICI B tranche — as 0.00%, and a revenue collapse from $5MM to zero as Revenue Trend: Decreasing rather than as no line at all. A field a caller never filled in is None, and only that renders as N/A.

NMTCTerms.qlici_b_rate is not an example of this, and an earlier version of this section used it as one. It is a required float, not an Optional, and it reaches neither rendering at any value — see the NMTC known limitation. The 0.00% above is LoanTerms.interest_rate, which does render.

The one exception is Optional[str], where the falsy value is the empty string — and any string that is only whitespace, which states exactly as much. An empty string states nothing, so there is nothing of yours for the memo to reproduce, and whatever it prints in its place is the package's own output standing in for your content.

There are 16 Optional[str] fields. For 15 of them what the package would print is a label it supplies — a heading, a table row label, a bold prefix — left standing with nothing after it: | Anticipated Closing | |, or ### Mission above a blank line, or a numbered condition that is just 2.. Six render as a heading over a body (description, mission, collateral, guarantor, use_of_proceeds, impact_narrative), five as a table row label (closing_date, maturity_date, cde_name, investor_name, and use_of_proceeds again, which is a Deal Summary row as well as a heading), and five as an inline bold label (ceo_name, website, census_tract, fund_name, ic_date — the last two render N/A and TBD, which is what an absent value renders too).

The sixteenth is deal_summary, and it is the exception to the label: it is reproduced as bare prose in the Executive Summary, with no heading, no row and no prefix of its own. An earlier version of this section said an optional string is always rendered behind a label, over a count of 16, and that sentence was false for this field. There is no label to orphan here and an empty string costs only a blank line; the field is inside the rule because the rule is uniform, and uniformity is what is guaranteed: for all 16, "" and " " produce a memo byte-identical to the one you get by leaving the field alone.

The same rule governs the elements inside conditions, so an empty condition is dropped and the rest are renumbered.

And a deal with no risks says so as a fact about its inputs. It does not claim the deal has no risks; the package has no way to know that.

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Risk Severities

RiskFactor.severity must be one of High, Medium or Low, matched case-insensitively — "high", "HIGH" and "High" are all accepted and normalise to High. Anything else raises ValueError. All the validated string fields (borrower_type, sector, deal_type, recommendation, severity) behave this way.

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Deal Types Supported

• loan — Direct loan or line of credit
• nmtc — New Markets Tax Credit investment
• equity — Equity investment
• grant — Grant or forgivable loan
• guarantee — Loan guarantee

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NMTC Deals

from creditmemo import NMTCTerms

nmtc = NMTCTerms(
    nmtc_allocation=10_000_000,
    credit_price=0.83,
    leverage_loan_rate=0.045,
    qlici_a_rate=0.045,
    qlici_b_rate=0.010,
    cde_fee_rate=0.02,
    cde_name="Chicago Development Fund",
    investor_name="US Bancorp CDC",
)

deal = DealProfile(..., nmtc_terms=nmtc, ...)

All rates above are fractions, not percentage points — 4.5% is 0.045. So is LoanTerms.max_ltv. The one exception in the package is FinancialData.ltv, which is in percentage points (a 75% LTV is 75.0); it raises if you pass it a fraction rather than render a false number. Unifying the two scales is the second item for 0.3.0.

Known limitation: four NMTC inputs do not reach the memo

As of 0.2.1, leverage_loan_rate, qlici_a_rate, qlici_b_rate and compliance_years appear nowhere in the generated memo — not in the Markdown, not in the Word document. The first three are required arguments: you cannot construct NMTCTerms without supplying them, and the package then discards them silently.

Measured by perturbing each field on NMTCTerms one at a time and diffing both renderings. Of the nine inputs:

Input	Reaches the memo?
nmtc_allocation	yes — QEI (NMTC Allocation), and the three derived figures
credit_price	yes — Credit Price, and Investor Equity
cde_fee_rate	yes — CDE Fee, and Estimated Net Subsidy
cde_name	yes — CDE
investor_name	yes — Tax Credit Investor
leverage_loan_rate	no (required argument)
qlici_a_rate	no (required argument)
qlici_b_rate	no (required argument)
compliance_years	no (defaults to 7)

For an NMTC deal the QLICI A and B rates and the seven-year compliance period are core structural terms. If you are using this package for an NMTC transaction, add them to your memo by hand until this is fixed. Adding rows changes the .docx table shape and needs the gate coverage that goes with it, which is why 0.2.1 discloses it rather than patching it. This is the top item for 0.3.0.

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Known Limitations in 0.2.1

Four things this release does not do, disclosed here because you would otherwise find them in a memo. Two more are in How Dollar Figures Are Written — one of which 0.3.0 removes and one of which is inherent to rounding and will not be removed — and one is in NMTC Deals.

Ratios, rates and the credit price still round a small non-zero to zero. 0.2.1's rounding work covers dollar figures only. The other formatters were not swept, and each renders a small supplied value as the characters a stated zero produces:

Field	Supplied	Renders
dscr, current_ratio, debt_to_equity, the three projected DSCRs	0.001	0.00x
interest_rate	0.00001	0.00%
ltv	0.0001	0.0%
min_dscr_covenant	0.001	Minimum DSCR of 0.00x
max_ltv	0.0001	Maximum LTV of 0.0%
origination_fee_pct	0.00001	0.00%
cde_fee_rate	0.0001	0.0%
credit_price	0.001	$0.00/$1

The DSCR is the figure an IC reads first. Fixing this means changing numbers across seven sites and needs the same gate coverage the money formatter got, so 0.2.1 discloses it. The one that bites on an ordinary deal rather than an unusual input is cde_fee_rate at one decimal, which cannot tell 2.04% from 2.0%.

Required strings are not checked, and None reaches the memo as the word None. The empty-string rule above governs the 16 Optional[str] fields. deal_name, prepared_by, prepared_date and the required BorrowerProfile strings are not optional, so the package takes them as given. With deal_name=None, prepared_date=None, prepared_by=" " and borrower.name=" " you get, with nothing raised:

# None
**Prepared By:**
**Date:** None
| Borrower |    |

fund_name, which is optional, correctly reads N/A three lines above. Until 0.3.0 decides between validating these at construction and giving them a placeholder, supply them. Assembling a DealProfile field by field is the route that hits this.

Non-Optional counters still treat 0 as absent. On ImpactData: affordable_units, sq_ft_community_space, patients_served, students_served, businesses_supported. On LoanTerms: io_periods and origination_fee_pct. None of them is Optional, so the row is suppressed on 0 and you cannot say "I checked, and it is zero" the way you can with the seven tri-state flags.

The Historical Financial Summary maps revenue_y1 to the column headed Year -2 — oldest first — and nothing in the memo or the field names says so. The stated Revenue Trend depends on that mapping. Renaming the fields or the columns is a breaking change to the input contract, so 0.2.1 documents it.

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Running Tests

pip install -e ".[docx]" pytest
pytest tests/ -v

The .docx gates skip if python-docx is not installed. Set CREDITMEMO_REQUIRE_DOCX=1 to make a missing python-docx an error instead — CI does this so the gates can never pass by being skipped.

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Who This Is For

• CDFI analysts drafting IC memos for loan committee
• Private credit teams standardizing deal documentation
• CDEs preparing NMTC investment memos
• Impact investors documenting community development deals
• Anyone replacing manual Word memo templates with structured Python inputs

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License

MIT 2026 Jaypatel1511