How to categorize bank transactions automatically

Knowing your account balance is not the same as knowing your spending. Categories — Groceries, Rent, Transit, Entertainment — turn a long list of debits into a budget you can act on. The hard part is assigning every line. Vereloop Finance automates most of that work after you upload bank statement PDFs, then lets you refine results with a short review and simple rules.

This guide walks through the full flow: parse, categorize, correct, and analyze. If you have not read why your bank PDFs need a parser, that article explains why structured data has to come before categories matter.

Step 1: Upload PDFs on Parse

Start on the Parse page. Upload one PDF per account per month — chequing for day-to-day spending, savings if you track transfers separately. The parser extracts each transaction with date, description, and amount. Without that step, there is nothing to categorize.

Upload two or three months when you first start. More history helps the system recognize recurring merchants and gives you a fair baseline before you change habits.

Step 2: Review auto-assigned categories

After parsing, Vereloop assigns a default category to each row based on merchant text and known patterns. Common payees like grocery chains, transit agencies, and streaming services map quickly. Ambiguous lines — e-transfers, ATM withdrawals, one-off shops — may land in General or Uncategorized until you fix them.

Spend five minutes on the first upload correcting obvious mistakes. Change “Coffee shop on Main” from General to Dining if that matches your budget. Each correction teaches the system your preferences for similar descriptions on future statements.

Step 3: Set rules for repeat merchants

Rules are the automation layer. When you assign a category to a merchant once, you can create a rule: “Always categorize payees containing LOBLAWS as Groceries” or “Map PRESTO to Transit.” Rules apply retroactively to uploaded data and to new uploads, so you do not re-tag the same coffee shop every month.

• Contains — match part of the description (flexible for messy bank text).
• Exact — match the full payee string when your bank always uses the same label.
• Amount range — optional guard for merchants that vary (e.g. utility bills).

Keep rules specific enough to avoid false matches. “Map anything with PAY to Utilities” will catch too much; “Map TORONTO HYDRO to Utilities” is safer.

Step 4: Analyze on the dashboard

Once categories are trustworthy, open the Analyze page. Filter by month, category, or account. Compare dining spend April versus May, or see what percentage of chequing outflows went to subscriptions. Charts and totals only reflect the categories you confirmed — garbage in, garbage out still applies, but a one-time review fixes most of it.

Category design tips

You do not need fifty categories. Start with ten to fifteen that match how you think about money: Housing, Groceries, Dining, Transport, Health, Subscriptions, Shopping, Savings transfer, Income, Fees. Split later if a bucket hides too much — for example, pull Subscriptions out of Entertainment when you are hunting recurring charges.

Align categories with questions you actually ask: “Can I cut $200/month?” is easier when Subscriptions and Dining are separate, not buried in Lifestyle.

Common pitfalls

• Skipping review — auto-tags are good, not perfect; one pass saves wrong trend charts.
• Mixing accounts — upload chequing and credit separately so transfers do not double-count.
• Overfitting rules — too-broad rules miscategorize; test on the last month before applying globally.
• Ignoring refunds — positive amounts should reduce category spend, not sit in Income unless they are true income.

What happens next month

Download the new PDF, upload to Parse, skim uncategorized rows, done. Rules handle repeat merchants; you only touch new payees. Within a few months your category set stabilizes and monthly review drops to minutes. That is the payoff of automatic categorization — not zero work, but no spreadsheet rebuild.