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Data Extraction

Extract data from documents

Turn any PDF, PNG, photo or scan into the same normalised JSON through our API, matched automatically against your application data. When Open Banking fails, you can still make a decision.

Book a demoSee how it works
High Street Bank · Current account
01–30 Sep 2026
−14.09
+2,150.00
−60.00
+340.00
−22.40
−118.75
Unstructured PDF
Same upload as the fraud check

A 14-page statement your team would normally read and key in by hand.

Account holder and account detailsName, address, sort code, account number
412 transactionsDate, description, amount, balance
Ready as JSON or CSVWith the fraud check on the same file
Extract

Toggle Extract: from PDF to data your systems can use.

JSON
One format, whatever the filePDFs, PNGs, photos and scans all come back as the same normalised data through the API, with the fraud check on the same upload.
Any file typeFrom any country, in any language
No page limiton extraction through the API
Structured dataExtract fields you deem essential

Used by financial crime, risk and credit teams

Portman Finance Group logo
Ultimate Finance logo
Carmoola logo
Moneybox logo
Halo Corporate Finance logo

What we extract

From any file to data you can decide on

Documents arrive in every format going. Fraudfinder reads them all, returns one consistent structure, and tells you where the data doesn't match what your customer told you.

PDFPNGSCAN
→
{ "name": "J. Okafor",
  "sort_code": "04-00-04",
  "balance": 3312.10 }
Same JSON · every format
01

Normalised from any file type

A PDF statement, a phone photo of a payslip or a scanned bill. Whatever arrives, you get the same clean JSON back through the API.

application  J. Okafor
document     J. Okafor-Reid
address      match
account      match
Name mismatch flagged
02

Customer data matching

Send us the details from your application. We extract the name, address and account details from every document and flag automatically where they don't match what your system holds.

{ "date": "2026-09-08",
  "desc": "Faster payment",
  "amount": 2150.00,
  "balance": 3312.10 }
412 transactions · JSON
03

An Open Banking alternative

When an applicant won't connect, or Open Banking fails, upload their statements instead. Every transaction, date, amount and balance comes back in the same structured shape.

What you can do with it
Affordability

Income, outgoings and balances ready for your rules.

Your own compliance checks

Run the raw data through the tests you already use.

Personal and account details

Names, addresses, sort codes, account numbers, IBANs and more.

Custom fields

Pull the data points your process needs (Enterprise).

Bank balance reconciliation

Check the transactions add up before you trust them.

Fraud check included

Forensics run on the same upload, so you never extract from a fake.

Every document

What we pull from the documents you see most

Any document, in any language, from any country. Here's what you get from the five that turn up most.

01Bank statements
  • Every transaction, date and amount
  • Opening, running and closing balances
  • Account holder, sort code and account number
  • And more
02Payslips
  • Gross and net pay, tax and NI
  • Employer and pay period
  • Employee name and reference numbers
  • And more
03Utility bills
  • Name and supply address
  • Account number and bill date
  • Address checked against the barcode
  • And more
04Invoices
  • Supplier, customer and invoice number
  • Line items, totals and VAT
  • Supplier bank details
  • And more
05Tax documents
  • Taxpayer details and tax year
  • Income and tax figures
  • Issuer and reference numbers
  • And more

One applicant, run through a typical stack

Your existing checks
ID and KYCPassed
Credit bureauPassed
Open BankingNot shared
+ Fraudfinder
The documents they sentBank statement, payslip
Edited

Everything else said yes. The statement had been changed.

Fits your stack

Streamlining for non-Open Banking flows

When applicants refuse to connect to open banking get structured data from the documents. Check for fraud in the same pass.

Live in under an hour, with a drag-and-drop portal

REST API into your decision engine when you're ready

Custom extraction fields on Enterprise

Proof

The teams already running it, in their words

Lenders, fintechs and gambling operators use Fraudfinder to stop fraud before the money goes out.

Who it's for

Used wherever a document decides the deal

If your team decides whether to trust a document, Fraudfinder does the checking behind that call. See how it works in your sector.

Get started

See documents turned into data

We'll run real statements and payslips through Fraudfinder and show you the extracted data and the fraud check, side by side.

Book your demo

We'll show you Fraudfinder catching real fraud, live.

Business email required. We'll never share your details.

Cyber Essentials certified. The UK government-backed cyber security standard.

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FAQs

Questions about data extraction

What data can you extract?

Transactions, dates, amounts and running balances from bank statements, plus names, addresses, sort codes, account numbers and IBANs, and the key figures from payslips, bills, invoices and tax documents. Fraudfinder can be trained to extract any key information you need for your processes.

What format does the data come back in?

JSON or CSV, normalised to the same structure whatever the file type (PDF, PNG, JPG or a scan), through the API or as a download from the portal.

Can it stand in for Open Banking?

It gives you the same shape of transaction data from a PDF statement, so you can still assess applicants who won't or can't connect through Open Banking. It's especially useful for overseas statements, banks that aren't on Open Banking, and applicants who refuse to connect.

Do you check the document for fraud too?

Yes. Every file gets a full forensic check on the same upload, so you never extract data from a fake without knowing.

Do we need to integrate before we can start?

No. Most teams start in the drag-and-drop portal and are live in under an hour, then move to the API once they've seen the results on their own files.

How does customer data matching work?

Send the applicant's details from your system with their documents. We extract the same fields from every file and flag any name, address or account details that don't match.

Is our customers' data safe?

Yes. We're ICO registered, Cyber Essentials certified, GDPR compliant and independently penetration tested, with UK and EU data residency. Our trust centre has the detail.

Document fraud detection and data extraction for lenders, brokers and financial institutions.

Cyber Essentials certified.

ICO REGISTEREDInformation Commissioner’s Office
CYBER ESSENTIALSCertified
GDPRCompliant

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