Analyze a bank statement with AI: what a chatbot gets wrong, and what to use instead

The short answer

A general chatbot such as ChatGPT can read a bank statement and give you a useful first look: rough categories, the largest merchants, a few charges worth questioning. It is not a record you can rely on. It can drop rows from a long PDF, add up totals wrongly without telling you, and start from nothing next month.

If you use one, check its answer against the statement with the three tests at the end. If you want the analysis to add up and to build month after month, use a tool that extracts the rows, lets you review them, and keeps them.

Pulget is one of those tools, and it also uses a language model to read statements. The difference is what happens around the model.

What a chatbot does well

Language models are good at the messy part of a statement: descriptors such as "POS 4471 BOLT.EU/O/2409 TALLINN" become "Bolt, taxi"; a table split across pages still reads as one table; and they read statements in many languages. For a one-off question ("what did I spend on food in March?"), that can be enough.

Where it goes wrong

• Rows go missing. A 10-page statement with 300 transactions is a lot of text. A chatbot may summarize part of it, or quietly work from the pages it read, and the answer may not say which.
• Totals are not checked. A model writes a total that looks right. Unless you ask, nothing compares it with the statement's own totals or balance.
• Categories drift. Ask again next month and the same merchant can land in a different category, so months stop being comparable.
• Nothing persists. Each conversation starts over. Three accounts and twelve months means pasting the same kind of document again and again, with no memory of what you already corrected.
• Currencies get added together. Unless told otherwise, a model may sum dollars, euros and manat into one number.

None of this means the model is useless. It means its answer is a draft, and a draft needs checking before you act on it.

What you share when you upload a statement

A statement carries your name, address, account number and a record of where you spend. Whatever you upload it to, the useful questions are the same: who stores it, who else processes it, whether it is used to train models, and how you delete it. A general chatbot answers these in its own data settings, which are worth reading before you paste in a statement.

For Pulget, the privacy policy answers them. Uploaded files and the data extracted from them are stored with Supabase. A language model reads each document through Google AI Studio or OpenRouter, using no-retention or no-training settings where the provider offers them. Pulget does not train models on your documents, and you can export or delete your workspace. It never asks for your bank login or a connection to your bank.

How a statement tool handles the same job

In Pulget the language model does the reading, and the rest is ordinary software you can check:

1. You upload a PDF, CSV, XLS or XLSX file to one of your accounts. Scanned PDFs are read with OCR first.
2. Pulget turns the file into rows: date, description, amount, direction and currency. Merchant names are matched against 887 known brands, and each row gets a category.
3. You review the rows before anything is saved. Anything read wrongly is corrected here, and the correction is reused the next time the same merchant appears.
4. You approve. A row the account already holds is skipped, so an overlapping statement does not count twice. Possible duplicates across different files go to Duplicates in the Review inbox, where you merge them or keep both.
5. Every approved transaction keeps a link to its source, so a figure in a report leads to its transactions, and each transaction opens the file and page it came from.

Because the rows are kept, the questions a chatbot answers once become reports that stay current: spending by category and month, income against spending, recurring charges suggested from your history, and totals converted into one reporting currency at each transaction's date.

Where a chatbot is enough

If you have one statement and one question, a chatbot is quicker than setting up any tool. It also costs nothing extra if you already pay for one. A statement tool earns its setup when you track more than one account, more than one month, or more than one currency. It also helps when someone else has to check the result, as with bank statements for your accountant.

If you still prefer a chatbot

Use a spreadsheet export rather than a PDF when your bank offers one, remove your account number and address first, and ask for a table rather than a summary:

Here is my bank statement. List every transaction as a table with the columns date, description, amount (negative for money out), currency and category. Do not skip or merge any rows. After the table, give the number of rows, the total money in and the total money out.

Then run three checks:

1. Count. Compare the number of rows with the statement. If the bank prints a count, use it; otherwise check the rows of one page against the table.
2. Reconcile. Opening balance plus money in minus money out should equal the closing balance printed on the statement.
3. Spot-check. Pick five rows at random, including the largest one, and compare each with the statement.

If any check fails, the categories built on top of it are not worth keeping.

Try it on one statement

Upload one month, free during preview, and compare what Pulget extracts with the statement before you approve it. Tracking spending without a bank connection explains the review step, pricing lists the file limits, and converting statements to CSV covers exporting the result.