Solution

Spreading Process Automation

For spreading teams, credit analysts, and data operations leaders at rating agencies, banks, and credit funds: annual reports extracted into your taxonomy at portfolio scale.

Annual reportsFinancial statementsBalance sheetsNotes to accountsAuditor reports
5× faster financial spreading100% of numbers cited to sourceHuman approval on every spread

The problem

Why this exists

50k+

Reports arrive faster than analysts can spread

One deployment faced roughly 200,000 bank annual reports, 50,000+ landing every quarter, across geographies, industries, and reporting conventions. Manual spreading cannot keep that pace.

The notes

Templates give up where the values live

Adjustments, restatements, and off-balance-sheet detail sit in non-standard tables and narrative notes — exactly the places template-based extraction fails.

Rekeying

Verification means typing it again

Checking a spread against the source means re-finding each figure in the report by hand. The verification step becomes its own bottleneck.

The product, not a promise

A spread you can interrogate

Spreading Process Automation — workspace
Balance sheet in your taxonomyMapped · citedcited
Off-balance-sheet detail from the notesExtracted from narrative textcited
Restatement adjustmentTraced to its notecited
Non-standard table, low-confidence cellFor analyst reviewverify
Output structureMatches downstream rating systemscited
HUMAN-APPROVED BEFORE IT POSTS

How it works

File in. Answer out.

  1. 1

    Intake

    Annual reports arrive in bulk — any geography, language convention, or reporting standard.

  2. 2

    Read

    Pre-trained table and financial-document models parse statements, non-standard tables, and the notes behind them.

  3. 3

    Map

    Extracted values land in your taxonomy — your line items, your industry variations, your structure.

  4. 4

    Verify

    Analysts review each figure side-by-side with the source page and approve or correct it.

  5. 5

    Deliver

    Approved spreads flow to downstream rating and credit systems in the format they expect.

Who it's for

Built for the people who own the outcome

Spreading analyst

You verify figures side-by-side with the source instead of rekeying them.

  • Every extracted number links to the page it came from
  • Non-standard tables and notes arrive parsed, with uncertain cells flagged
  • Corrections feed the models, so accuracy compounds with your work

Data operations leader

Quarterly report volume stops setting your headcount.

  • Spreading runs 5× faster than the manual process
  • 50,000+ reports per quarter handled in the reference deployment
  • Output lands in the exact structure downstream systems expect — zero reformatting

Risk & compliance

No figure moves downstream without lineage and a named approval.

  • 100% of numbers cited to their source page
  • Every spread carries human approval before it feeds a rating or credit system
  • The full trail — source, extraction, correction, approver — is there for review
Rating agenciesCommercial bankingPrivate creditPortfolio monitoringCovenant trackingCredit funds
faster spreading
Thousandsof annual reports per quarter, one deployment
100%numbers cited to source
Humanapproval on every spread

From annual report to approved spread

Financial spreading is where credit analysis slows down. A large American financial services and rating agency faced the problem at scale: roughly 200,000 bank annual reports to process, 50,000+ arriving every quarter, across many geographies, industries, and regulatory conventions. The data points varied by industry. The hardest values sat in non-standard tables and in the notes — the places template-based extraction gives up.

Botminds reads the whole report the way an analyst does. Pre-trained table-understanding and financial-document models handle the statements; the same models comprehend the notes and description text where adjustments, restatements, and off-balance-sheet detail actually live. On top of that base, the platform learns the client’s own taxonomy — industry-specific line items, naming conventions, and the exact output structure their downstream systems expect. Each report converts to that structure immediately, with every extracted number linked back to the page it came from.

Why governed matters here

A rating agency cannot publish a figure it cannot trace. That constraint shaped the design: analysts verify extractions side-by-side with the original document, every value carries its source citation, and nothing moves downstream without human approval. Verification stops being a manual rekeying exercise and becomes a review step — which is how the client eliminated its verification bottleneck without loosening compliance.

This is the same spreading engine that powers Botminds lending and credit-decisioning work: document-to-decision, with the decision auditable. If your team spreads financial statements — for ratings, underwriting, portfolio monitoring, or covenant tracking — the intake formats change; the flow does not.

Objections, answered

What teams ask us first

How do I trust an extracted figure enough to publish on it?

Every number carries a citation to the page it came from, and analysts verify each figure side-by-side with the original document. Nothing moves downstream without human approval — the constraint a rating agency operates under shaped the design.

Our taxonomy has industry-specific line items and naming conventions.

The platform learns your taxonomy on top of its pre-trained financial models: your line items, your industry variations, and the exact output structure your downstream systems expect. Each report converts to that structure immediately.

What about non-standard tables and the notes to accounts?

That is where the pre-trained models earn their keep. They read the whole report the way an analyst does — statements, non-standard tables, and the narrative notes where adjustments and off-balance-sheet detail actually live. Low-confidence extractions are flagged for review rather than passed through.

How fast does this reach real volume?

Pre-trained table and financial-document models carry the general workload from day one; configuration is your taxonomy and output structure. The reference deployment sustained 50,000+ reports per quarter at 5× the manual spreading pace.

Bring your hardest annual report.

Watch statements, notes, and non-standard tables land in your taxonomy with every number cited.

Request a demo