πŸ“‚ CSV Auto Import β€” Usage Guide

How to Find Hidden Subscriptions in Your Bank Statement

8 min read Β· Privacy Finance Β· Browser Tools Β· No-Cloud Analysis

Most people are overpaying for subscriptions they've forgotten about. This guide shows you exactly how to export your bank CSV, detect every recurring charge using our local keyword engine, and export findings to Incinerator for a full audit.

Why "Vampire" Subscriptions Are Hard to Spot

Subscription services are engineered to stay invisible. They charge small amounts, use obscure billing descriptors (ever seen APNITMN*SERVICES on your statement?), and time renewals to your paycheck so they blend in with normal spending. The average person has 3-5 subscriptions they've completely forgotten about.

Traditional budgeting apps require Open Banking access β€” handing a third party your bank credentials 24/7. CSV Auto Import offers the same detection power with zero data exposure.

Step-by-Step: Export and Analyze Your Bank Statement

01

Export a CSV from your bank

Log into online banking β†’ Statements β†’ Download / Export β†’ Select CSV format. Chase, Revolut, Wise, MUFG, Shinsei, Rakuten Card β€” all support this. Choose a 3-month window to catch quarterly charges.

02

Drop the file into the upload zone

Drag and drop your CSV onto the tool, or click "Browse Files." The file is parsed locally by PapaParse β€” no network request is made. Your banking data stays in your browser's RAM.

03

Review the detected matches

The tool flags every row containing a subscription keyword. Check each match β€” you may find services you forgot existed. Uncheck false positives (like "RENEWAL" appearing in a non-subscription transaction).

04

Export to Incinerator

Click "Bulk Add to Incinerator" to send your confirmed subscriptions to the Incinerator audit suite for ongoing tracking and cancellation planning.

πŸ”’ Zero-Upload Verified Open DevTools β†’ Network tab, then upload your CSV. You'll see zero outbound requests containing your financial data. The detection engine runs 100% client-side.

How the Keyword Detection Works

The tool matches each CSV row against a curated database of 200+ global patterns:

The detection is case-insensitive and works regardless of column order in your CSV.

// Detection logic (simplified):
const row = "2024-03-15, SPOTIFY PREMIUM, -14.99, USD"
const match = KEYWORDS.some(k => row.toUpperCase().includes(k))
// β†’ true (matches "SPOTIFY")

Tips for Better Detection

Frequently Asked Questions

Is my bank CSV data safe?

Yes. PapaParse reads the file in your browser's RAM. No server upload occurs. Refreshing the page clears everything β€” nothing is persisted.

Which bank formats are supported?

Any standard CSV. The smart-detection algorithm handles varying column orders automatically β€” Date, Amount, and Description can be in any position.

What if my subscription uses an obscure billing name?

The generic patterns ("Subscription," "Membership," "Recurring") catch most non-branded charges. For anything unusual, scan the "Potential Match" list for unfamiliar recurring amounts.

Can I detect annual or quarterly charges?

Yes β€” upload a 12-month statement to catch annual renewals. The keyword match doesn't depend on charge frequency.

Find Your Hidden Subscriptions Now

Drop your bank CSV and get a full subscription audit in under 30 seconds.

Open CSV Auto Import β†’