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TUE · SEP 8 · EDITION |
A repeatable AI extraction workflow for client documents
This workflow replaces the manual pass through a bank statement, loan schedule, or tax form where someone reads the PDF and types values into a spreadsheet one field at a time. It is built for staff accountants doing monthly bookkeeping close or document prep, and it works fastest on text-based PDFs where the AI can actually read the content. The prompt returns a numbered list with field name, extracted value, and the page it came from - so the required human review has a clear structure to work against.
BUILD WITH AI
How to build a client document extraction workflow with an AI assistant
Before you start, gather the client documents in one folder and decide exactly which fields you need - the prompt only works as well as your field list. This workflow runs fastest on structured, text-based PDFs.
1 |
Collect the client documents for the period (bank statement, loan schedule, or tax form) into a single named folder and confirm you have the correct version from the client. |
2 |
Open your general-purpose AI assistant and upload or paste the document text. |
3 |
Paste this extraction prompt: 'You are an accounting data assistant. From the attached document, extract the following fields and return them as a numbered list with the field name, the extracted value, and the page or section where you found it. Fields: entity name, document date, opening balance, closing balance, total deposits, total withdrawals, any line items flagged as unusual or over |
4 |
Review the numbered output field by field against the open source document - do not close the PDF during this step. |
5 |
Flag any field marked NOT FOUND and any value that does not match the source exactly; correct these manually before moving to the next step. |
6 |
Paste the corrected output into your working file or spreadsheet using the same field order every time, so downstream reconciliation steps have a consistent structure. |
7 |
Log the document name, date processed, and the name of the reviewer in your job notes before closing the file. |
WORKED EXAMPLE
In practice
A business client has uploaded their June bank statement - a 14-page text-based PDF - for the monthly bookkeeping close. The staff accountant needs to pull opening balance, closing balance, total deposits, total withdrawals, and any single transaction over $10,000.
What came back. The assistant returned all six fields with page references and listed three transactions over $10,000. Two matched the statement exactly. The third listed a wire transfer amount that was off by $1,000 - the assistant had read a fee line on the same row as part of the transaction total. The entity name also came back without the LLC suffix, which matters for the engagement file.
How it was checked. The staff accountant opened the PDF to the page cited for each field and confirmed the figure character by character before entering values into the reconciliation workpaper.
A constructed example. The prompt is usable as written; the figures show the shape of a result, not a measured one.
WHEN TO USE IT
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An original workflow written for practitioners. Replicate it in a sandbox first; nothing here replaces your review.
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