Bank statement analysis and transaction categorization
Upload statements as PDF, XML or JSON, or send transactions through the API. Get categorized transactions, custom risk flags, PDF fraud checks and currency conversion.
API Integration
RESTful cloud API. Set up in days, not months. No prior data formatting required.
Web Cabinet
No developers needed. Upload bank statements and get instant categorized results online.
PDF + JSON/XML
PDF statements from 100+ European banks, plus universal JSON/XML open banking formats.
80+ Categories
Salary, rent, groceries, utilities, gambling, crypto – granular category coverage.
More than categories: what you get from every statement
Transaction categorization
Every transaction receives a standard category such as groceries, subscriptions or utilities, even when the merchant text is messy or inconsistent. Accuracy is 96% on the Baltic, Romanian and German bank data we process, and a whole statement is typically categorized in under 2 seconds.
Custom risk flags
Lenders can reproduce their own credit policy rules on top of the categories. Build a flag in the flag setup section from totals, averages, counts, amounts or fluctuations of a category, compare one category with another, or calculate ratios between flags you have already defined.
PDF fraud checks
Uploaded PDF statements are checked for signs of editing with detection methods we have built in-house. When we are sure a PDF has been edited, you receive an error straight away instead of results. The check works on the most popular bank PDFs.
Currency conversion
When you upload several statements in different currencies, all amounts can be converted to the currency you use, so totals and flags compare like with like.
From raw statement to structured data
Send statements or transactions
POST bank statement lines or PSD2 transaction data to the API (or upload in our web portal) — PDF, XML, JSON, or a direct feed from your AIS integration.
Get structured results back
Each transaction returns a category (e.g. groceries, subscriptions, utilities), and your custom risk flags are calculated on top. A PDF that is identified as edited is rejected with an error. A whole statement is typically processed in under 2 seconds.
Use it in your product
Power budgeting views, spend analytics, credit scoring inputs, or bookkeeping automation — without building and maintaining your own classifier.
Bank statement analysis, answered
What is bank statement analysis?
It means turning raw bank statements into structured data you can act on. At Catego that includes categorizing every transaction, checking PDF statements for signs of editing, converting amounts to one currency, and calculating custom risk flags that mirror a lender's own credit policy.
What are custom risk flags?
Flags are rules you define on top of categorized transactions, for example a total, average, count or fluctuation within a category, a comparison between two categories, or a ratio between other flags. You build them in the flag setup section, and for each flag you can see which transactions triggered it. Lenders use them to apply their internal credit policy consistently and to calculate key metrics quickly.
Does Catego detect edited PDF statements?
Yes, for the most popular bank PDFs. When we are sure that a PDF has been edited, you get an error message immediately. The check does not cover every one of the 100+ banks whose PDFs we can read, and we don't publish how the detection works.
Can statements in different currencies be combined?
Yes. When you upload several statements in different currencies, amounts can be converted to the currency your client uses. The conversion uses the current day's exchange rate.
What is bank transaction categorization?
It's the process of automatically tagging raw bank transaction lines — which usually arrive as messy, inconsistent merchant strings — with a standardized category, such as groceries, transport, or subscriptions. It turns raw statement data into something a budgeting app, accountant, or credit model can actually use.
Which statement formats are supported?
PDF statements from more than 100 banks, XML files (ISO 20022), and JSON from the largest AIS providers. You can also send transactions directly from our own PSD2 open banking service.
How accurate is Catego's categorization?
Categorization accuracy runs at 96% across the transaction volumes we process for Baltic, Romanian, and German bank data — see the stats on our homepage for current figures.
Does this work with PSD2 open banking data?
Yes — categorization pairs naturally with our AISP/open banking service, so you can pull transactions via PSD2 and categorize them in the same pipeline. They're also available as fully separate services if you already have your own data source.
What banks and markets are supported?
PDF statements from more than 100 banks are recognized. Categorization models are adjusted for high categorization quality in the Baltic states, with additional coverage in Romania and Germany. Other markets would see lower categorization accuracy.
Who uses bank statement analysis
Affordability checks for lenders
Replace uploaded PDF statements with a consented bank connection and categorized transactions.
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Sync company bank transactions into bookkeeping and reconciliation without XML or CSV imports.
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Show customers all their accounts and categorized spending in one place.
Read more →Credit risk & scoringStatement analysis for credit scoring
Turn statements from any source into categories, risk flags and fraud-checked data your credit process can use.
Read more →Need raw transaction data too?
Pair bank statement analysis with our licensed PSD2 open banking (AISP) service to pull transactions directly through our 17 bank connections.