How to Analyze Your Credit Card Statement With AI (Free Mint Replacement)
Mint shut down in March 2024 and a lot of people never replaced it. You do not need a new app: download your card transactions as a CSV from your bank, strip the account numbers, and drop the file into ChatGPT or Claude. Here is the exact prompt that finds forgotten subscriptions and category creep, plus the privacy checklist to run first.
The statement email lands, you open it, and you do the thing everyone does: stare at the total, scroll the list once, recognize maybe half the merchants, and close the tab. Mint used to catch what that scroll misses. Then Intuit shut it down on March 23, 2024 and pointed everyone to Credit Karma, which does not do Mint-style category budgets. Some people moved to YNAB or Monarch and pay for them happily. A lot of people did neither, and their spending has been running unaudited ever since. If that is you, here is the free version: your card's own CSV export plus a chatbot. It will not track you daily like Mint did, but for a quarterly "where is my money actually going" audit, it is honestly better, because you ask the questions.
Why the raw CSV beats an app's auto-categories
Your card's transaction export is the unfiltered record: every merchant, every amount, every date. Budget apps auto-bucket that for you, which is convenient right up until "Amazon" swallows groceries, gifts, and impulse buys into one useless category. Feed the raw file to an AI instead and you set the rules, then change them mid-conversation. That flexibility is the whole trick.
Step 1: export the last three months
Log in to your issuer's site or app, open transactions (sometimes under statements), set the range, and hit export or download. Nearly every major US issuer offers CSV. One month is noise; three months is a pattern. If you use multiple cards, export each and upload them together, the AI will merge them.
- 01Log in to your issuer
Website or app
- 02Open transactions
Or the statements page
- 03Set 3-month range
Patterns need history
- 04Download CSV
CSV over PDF if offered
Step 2: strip the file before it leaves your machine
This is the step that matters. A statement carries identifiers you should never hand to any third party, chatbot included.
- Card or account number
- Your name and address
- Reference or authorization codes
- Transaction date
- Merchant name
- Amount
Date, merchant, amount. That is the entire dataset the analysis needs. Two more habits: turn off model training on your data in the app's settings (ChatGPT and Claude both offer this), and if a specific row feels too personal, just delete the row. The audit survives missing a few lines.
The money-leak prompt
Upload the sanitized file (or paste the rows) and send this:
You are my no-nonsense budget auditor. Use ONLY the transactions I uploaded.
My categories: groceries, dining out, coffee/snacks, transport,
subscriptions, shopping, other.
1. Total and share per category, largest first, in a table.
2. List every recurring charge (same merchant, similar amount, monthly).
3. Which category grew the most from month 1 to month 3, and by how much?
4. Flag 3 charges I might not be using, with your reasoning.
5. Recheck: do the category totals add up to the statement total?
On a three-month sample this is the shape that comes back (merchants and amounts below are an illustrative example):
By category (monthly average, example): dining out 388 > subscriptions 71
Recurring charges: 10.99 music on the 11th, $12.99 cloud storage on the 22nd
Fastest-growing: coffee/snacks, +43% from month 1 to month 3
Possibly unused: cloud storage $12.99. No other activity from that service in the whole file
Recheck: category totals match the statement total. Note: 9 "MKT PLACE 4412" rows were guessed as groceries, please confirm
Items 4 and 5 do the real work. Four is the forgotten-subscription detector, the modern version of what Mint's recurring view did. Five forces the model to check its own math, which matters because totaling long tables is exactly where chatbots quietly slip.
Where this beats an app, and where it does not
FAQ
What replaced Mint after it shut down?
Intuit closed Mint on March 23, 2024 and pointed users to Credit Karma, which does not replicate Mint's category budgeting. Paid apps like YNAB and Monarch Money picked up many users. But if what you mainly want is a monthly "where did my money go" audit, a chatbot plus your card's CSV export does that for free.
How do I download my credit card transactions as a CSV?
Log in to your card issuer's website or app, open the transactions or statements page, set the date range, and look for an export or download button. Nearly every major US issuer offers CSV export. Pull the last three months rather than one, so patterns show up instead of one-off noise.
Is it safe to upload my card statement to ChatGPT?
Only after you strip identifying data. Delete the account number, your name and address, and any reference numbers; keep date, merchant, and amount, which is all the analysis needs. Also turn off model training on your data in the app settings (both ChatGPT and Claude let you). If any row feels too sensitive, delete it; the analysis survives.
Can AI actually find money leaks in my spending?
It is good at exactly that: recurring charges you forgot, categories that crept up over three months, and duplicate or unusual charges. It is less reliable at totaling long tables and at guessing what a vague merchant name was. Give it your own category rules and ask it to double-check totals against the statement balance.
My honest take
I run this once a quarter and treat it like a dental checkup: slightly unpleasant, over quickly, occasionally finds a cavity. The last run surfaced a cloud subscription I had not opened in months. No app, no subscription fee, about ten minutes end to end. The one non-negotiable is the sanitizing step; the two minutes it takes are the price of doing this safely.