How to Turn a Messy Bank CSV into a Tiller-Ready Table in Google Sheets™

A bank export does not need to be perfectly tidy before you bring it into Google Sheets™. The Text To Table Converter add-on can load a CSV from Google Drive™, remove report clutter, and shape the transaction rows for Tiller with the Table Editor's target-format preset.

Last verified: July 28, 2026.

Bank exports often include a title, account details, blank spacer rows, repeated headers, opening or closing balances, and a transaction list that does not quite match the columns you want. Google Sheets™ can open the file, but cleaning the report into a consistent transaction table is still manual work.

This walkthrough uses a sample file named bank-export-messy.csv. It shows how to start from Google Drive™, choose Tiller, review the instructions that the preset sends to the AI, and insert the cleaned result into a new sheet.

What the Tiller preset does#

The Tiller choice is a starting instruction for the conversion. It tells the AI to prepare a bank transaction table using fields such as:

• Date
• Description
• A signed Amount, or a compatible amount-plus-type or inflow/outflow layout

It also asks the conversion to use MM/DD/YYYY dates, keep a date on every transaction row, and remove preambles, blank spacer rows, and totals.

The preset does not connect to Tiller, upload the result to a Tiller account, or guarantee that an ambiguous transaction has been categorized correctly. Treat the result as a clean starting table and review the values before importing it into any financial workflow.

Step 1: Open Convert selection without selecting cells#

1. Open the Google Sheet™ where you want the result.
2. Open Extensions > Text To Table Converter > Open Sidebar.
3. Leave the sheet without a selected data range.
4. In the sidebar, expand Tables & Convert if needed.
5. Click Convert selection in the Text to Table section.

The add-on opens the HTML Create a Table modal. Because no cells are selected, it asks which source you want to convert instead of trying to parse the current sheet.

Step 2: Load the CSV from Google Drive™#

1. Select the From Google Drive tab.
2. Click Pick from Google Drive™.
3. Select bank-export-messy.csv.
4. Wait for the selected filename and size to appear.
5. Click Next.

The Next button moves from choosing the source file to the optional instructions step. It is not the final conversion button yet.

Step 3: Choose Tiller as the target format#

The next screen is titled Instructions for the AI. The instructions box can be left blank for a basic conversion, or you can describe how the result should be organized.

1. Open the Target format menu.
2. Under Budgeting & accounting, choose Tiller.
3. Read the populated instruction in the text box.
4. Add a small clarification if the export needs one, such as keeping a specific merchant column or excluding transfer rows.

Selecting Tiller fills the instructions box; it does not create a separate export template. If you edit the text manually, the selection returns to Custom so it is clear that you are using your own instruction.

Step 4: Create and review the table#

1. Click Create from File.
2. Wait while the CSV is parsed and the instructions are applied.
3. Review the table in the editable grid.
4. Correct any ambiguous dates, descriptions, signs, or rows before inserting it into the sheet.
5. Click Insert Table when the result is ready.

For a simple bank export, the result may look like this:

Date,Description,Amount
01/02/2026,Opening deposit,1250.00
01/04/2026,Neighborhood Market,-48.63
01/06/2026,Payroll deposit,2200.00

The exact columns depend on what the source file contains. A source with separate credit and debit columns may retain that structure, while another export may be easier to represent with one signed Amount column.

Review the result before importing it anywhere#

Financial data deserves a quick human check even when the table looks tidy:

• Confirm that every transaction has the correct date.
• Check whether money out is negative and money in is positive when using signed Amount.
• Look for duplicated transactions created by repeated report sections.
• Check opening balances, closing balances, and subtotal rows.
• Review transfers and refunds, which may need special handling in your accounting workflow.
• Remove account numbers or other sensitive columns that you do not need.

If the result needs another change, use the Table Editor grid or run an AI Assist instruction such as Remove transfer rows and keep the original transaction descriptions. Make the instruction specific, then review the edited cells before inserting the table.

If the file is still not clean#

The Tiller preset is most useful when the file contains identifiable transaction rows but also includes report clutter. If the export has several unrelated sections, split the file into one report section at a time or add a precise instruction describing which section to keep.

If Google Drive shows the file as loaded but the first screen still appears, click Next. The file-selection screen uses Next to continue; Create from File appears on the following instructions screen and starts the conversion.

Create a cleaner starting point for Tiller#

The workflow is: load the messy export, choose the target format, review the AI instruction, and inspect the resulting rows before they reach your spreadsheet. That saves the repetitive cleanup while leaving the financial decisions in your hands.

Get the Add-On#

Get the Add-On - Free

Text To Table Converter

Turn messy CSV exports into reviewable tables: Install Text To Table Converter to load CSV files from Google Drive™, apply a Tiller-oriented conversion instruction, and review the result in Table Editor.

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Related Guides#

• Convert Text to Table - Learn the supported inputs and conversion options.
• Text to Table Workflows - Compare direct insertion, Table Editor review, and file-based starts.
• Table Editor - Edit, format, and insert the converted table.