Business profit and loss spreading inputs
For Credit analysts preparing income statement spreads
Prepare period, revenue, expense categories and stated net income from a p&l with fields you can edit. No lender adjustments.
25 free credits/month · No card needed
See the workflow and review checksInspect a document example.
Synthetic documents · Expected output- business name
- Example Harbor Services LLC - synthetic
- period start
- 2026-09-01
- period end
- 2026-09-30
- revenue rows
- [ { "category": "Example category - synthetic", "period_label": "September 2026", "description": "Example document line - original synthetic data", "amount": 1250 } ]
- expense rows
- [ { "category": "Example category - synthetic", "period_label": "September 2026", "description": "Example document line - original synthetic data", "amount": 250 } ]
- stated revenue
- 1250
- stated expenses
- 250
- stated net income
- 1000
{
"business_name": "Example Harbor Services LLC - synthetic",
"period_start": "2026-09-01",
"period_end": "2026-09-30",
"revenue_rows": [
{
"category": "Example category - synthetic",
"period_label": "September 2026",
"description": "Example document line - original synthetic data",
"amount": 1250
}
],
"expense_rows": [
{
"category": "Example category - synthetic",
"period_label": "September 2026",
"description": "Example document line - original synthetic data",
"amount": 250
}
],
"stated_revenue": 1250,
"stated_expenses": 250,
"stated_net_income": 1000
}A complete synthetic document with the visible values shown below. Real responses also include model-reported confidence, validation and result status. Test your own file with this schema.
When this work lands on your desk
A p&l arrives for credit analysts preparing income statement spreads. The next step needs period, revenue, expense categories and stated net income, recorded under the correct document reference before the information enters your loan intake worksheet.
An expense is shown in parentheses while the report displays a positive subtotal. Preserve the sign and reported subtotal without making lender adjustments. This schema keeps the source labels and values explicit so the reviewer can resolve the issue before downstream use.
Start with the documents you already collect
- P&L PDFs
- Scanned or photographed p&l pages
PDF, JPEG, PNG, TIFF, or WEBP. Send one file per extraction call; create separate schemas when the document types need different fields.
Define the fields
Open the starter schema. Edit field descriptions, mark the values your process requires, and save it in your account.
Extract at intake
Send the document and saved schema slug to
POST /api/v1/extract, or collect the file through a branded upload site.Hand off reviewed data
After checking business name, period start, period end, your application maps the reviewed record into your loan intake worksheet. Keep the original document reference with the result. No lender adjustments. Dokyumi processes one file with a saved schema; your application owns record matching, business rules and updates to other systems.
A schema shaped around the next step.
Start with these fields, then adjust them to match your documents and destination system. The example above shows the data object you are asking Dokyumi to extract.
Download editable starter schemaChoose required fields for your process. The starter schema preserves any defined nested fields; refine line-item structures and test them on representative files.
| Field | Type | What to capture |
|---|---|---|
business_name | string | Business name exactly as printed in this p&l. Preserve identifiers and qualifiers; do not look up or infer missing information. |
period_start | date | Opening date printed for the reporting period, separate from the issue date. |
period_end | date | Closing date printed for the reporting period, separate from payment or posting dates. |
revenue_rows | array | Every visible revenue rows row in this p&l. Preserve separate rows, labels and qualifiers; do not merge entries or reconstruct missing ones. |
expense_rows | array | Every visible expense rows row in this p&l. Preserve separate rows, labels and qualifiers; do not merge entries or reconstruct missing ones. |
stated_revenue | currency | Stated revenue explicitly labeled in this p&l. Preserve its sign and stated currency; do not calculate a missing amount. |
stated_expenses | currency | Stated expenses explicitly labeled in this p&l. Preserve its sign and stated currency; do not calculate a missing amount. |
stated_net_income | currency | Net income as printed for this period; do not calculate underwriting income or adjusted NOI. |
Give exceptions a clear path to review.
Dokyumi returns a model-reported confidence map, validation details, and a completed or review status for produced results. Check required fields and your business rules before passing data onward.
A completed extraction describes the extraction result. Your application and reviewers own matching, approvals, routing, and updates to other systems.
Read the response contractChecks for this process
- An expense is shown in parentheses while the report displays a positive subtotal. Preserve the sign and reported subtotal without making lender adjustments.
- Check period start, period end against their own printed labels; leave an unstated date empty instead of deriving it.
- Check stated revenue, stated expenses, stated net income for signs, decimal placement and stated currency before any downstream calculation or posting.
- Compare every revenue rows, expense rows row with the source, including continuation pages, separate categories and repeated table headings.
Prove the fit on a representative batch.
Test p&l examples from the layouts your team actually receives. Include the exception described here: An expense is shown in parentheses while the report displays a positive subtotal. Preserve the sign and reported subtotal without making lender adjustments. Compare the extracted business name, period start, period end and any line rows with a reviewer's checked reference before enabling downstream actions.
Compare extracted values with a reviewer’s reference set. Record corrections, unresolved fields, review time, and credits used before connecting downstream actions.
The free plan’s credit limits apply. Assisted pilots are scoped with Dokyumi before work begins.
Expand when the next process is ready
Add recurring extraction capacity when p&l intake becomes routine. Reuse this field contract for layouts that express the same information; create a separate schema when the next document has different fields or review requirements.
For a tailored implementation
Discuss document volume, page lengths and schema setup for credit analysts preparing income statement spreads. Bring difficult p&l samples and the review requirements your implementation must preserve.
Talk through document mix and volumeStart small. Add capacity as intake grows.
All self-service plans include the REST API, upload-site webhooks, custom confidence thresholds, and schema inference. Choose by volume, schema count, and upload sites.
Each document uses one credit per 5 pages, rounded up. An 8-page file uses 2 credits. Self-service files can be up to 50 pages; larger files, custom-built schemas, and additional volume are quoted through Enterprise. Full pricing details
Questions about business profit and loss spreading inputs
Which fields can I capture from a p&l?
The starter schema contains business name, period start, period end, revenue rows, expense rows, stated revenue, stated expenses, stated net income. Edit those definitions and choose your required fields before saving. Array fields include defined sub-fields so row values have a validation structure.
What needs review in business profit and loss spreading inputs?
An expense is shown in parentheses while the report displays a positive subtotal. Preserve the sign and reported subtotal without making lender adjustments. Check the original source alongside model-reported confidence and validation output; completion status describes the extraction result, not the business decision.
How does this data reach your loan intake worksheet?
Save the schema, then send one supported PDF or image to POST /api/v1/extract with its slug. The response contains the data, model-reported confidence, validation and result status. Your application maps reviewed values to the destination; upload-site submissions can use a configured webhook. No lender adjustments.
How do I test this workflow on my own documents?
Start free with 25 credits per month, 2 schemas, and 1 branded upload site. The starter schema opens in the schema builder after sign-up. Edit the fields, save it, and upload a representative file through your account or the extraction API. Account documents are stored according to Dokyumi’s privacy policy; contact hello@dokyumi.com for deletion requests and retention requirements.