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    Accounting · Mid-Market

    Turning Check Images and Bank Statements Into Usable Data

    PythonGoogle DriveExcel
    The workflow, visualized

    From friction to flow.

    Watch the work re-shape itself — the same steps, restaged so the team can move.

    Accounting workflow

    Python · Google Drive · Excel

    Seconds · Let the parser highlight the target check and surface the vendor instantly.

    Before
    2–10 min
    Per check, scrolling the bank's check PDFs
    After
    Seconds
    Tool highlights the right check on screen
    The challenge

    Where the friction lived.

    Accountants at a Westchester CPA firm were spending 2 to 10 minutes per check manually matching handwritten check images to transactions in QuickBooks. The bank exports a PDF with all the check images, but finding the right one is a grind. You see a check number and amount in QuickBooks, but the vendor name is missing. So you scroll through pages of scanned checks trying to match it. With active clients writing hundreds of checks per year, this added up fast. On top of that, monthly bank statements were being transcribed by hand into spreadsheets, taking about 15 minutes per statement.

    The check reader alone turns a 2 to 10 minute search into a few seconds. Multiply that across hundreds of checks and the math speaks for itself. The bank statement parser removes 15 minutes of manual data entry per statement, and the firm processes hundreds of these per year. These tools are taking some of the most tedious work in the office and making it disappear.

    Implementation

    How we built it.

    1. 1Analyzed the structure of the bank's check export PDFs to understand how check images and data are organized
    2. 2Built a parser that extracts check identifiers and highlights the target check on screen
    3. 3Analyzed the bank's statement PDFs and mapped every data field to a structured format
    4. 4Built a second parser that converts bank statements into formatted Excel output
    5. 5Added detection logic so both tools recognize new matching PDFs automatically
    6. 6Tested against real client documents across multiple account types and statement periods
    The result

    What changed.

    ~15 min
    Saved Per Bank Statement
    • Check identification reduced from 2 to 10 minutes down to seconds
    • Bank statement transcription eliminated entirely (15 minutes saved per statement)
    • Both tools auto-detect matching PDFs when they appear in Google Drive
    • Accountants spend less time on data entry and more time on actual accounting work

    Matching checks used to be the worst part of my week. Now I just pull it up and the answer's right there.

    Staff Accountant
    CPA Firm, Westchester, NY

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