Heyyel Data ExtractorHeyyel Data Extractor

Bank Statement Data Extraction

Turn bank statements into structured transaction data

Extract account details, statement periods, balances, transaction dates, descriptions, debits, credits and custom fields from bank statements without entering the information manually.

Extract bank statement data → See statement fields
77 languages Editable fields JSON & CSV 1 credit per page
bank_statement_august.pdf
NORTH BANK
Monthly account statement
Statement period
01–31 Aug 2026
DateDescriptionDebitCredit
04/08Office Supplies€180—
08/08Client Payment—€2,400
14/08Software€320—
21/08Transfer—€1,150
Closing balance€11,290.00
Currency → EUR
Debit → €180.00
Balance → €11,290.00

The bank statement problem

Transaction data is useful only when you can work with it

Bank statements can contain dozens or hundreds of transactions across multiple pages. Finding the values you need and moving them into a structured format quickly becomes repetitive — especially when the same process is repeated every month. This is exactly the type of workflow where automating manual document data entry can reduce unnecessary copy-paste work. For a step-by-step walkthrough, see our guide to automating bank statement data extraction from PDFs.

Bank statement data extraction lets you retrieve selected account and transaction information as structured fields instead of reading every row manually.

Capture account informationAccount holder, account number, currency and statement period.
Extract balancesOpening balance, closing balance and other selected totals.
Structure transactionsDates, descriptions, debits, credits and references.
Prepare data for reviewExport selected statement information into a usable format.

Bank statement fields

Choose the account and transaction data you want to extract

Select Bank Statement as the document type and start with suggested fields. Edit them, add extraction hints, or add information specific to your workflow. If your statement process needs fields outside the preset, the same setup can be extended through custom data extraction.

Bank Statement preset
Editable extraction structure
Selected
account_holderText
account_numberText
statement_periodObject
currencyText
opening_balanceNumber
closing_balanceNumber
transactionsArray
Add custom field+

Transaction structure

Extract more than a single balance

Bank statement extraction can include repeating transaction data as well as account-level information.

01
Account-level fields

Holder, account reference, period, currency and balances.

02
Transaction-level fields

Date, description, debit, credit, amount and reference.

03
Your own fields

Add transaction category, internal tag, counterparty or another business-specific value.

Counterparty Transaction reference Category Internal tag

Different statement layouts

Extract the same transaction fields across different bank statement formats

Banks use different page structures, column labels and transaction layouts. The information your workflow needs can remain consistent even when the document changes — one of the reasons AI document data extraction is useful for statement collections that do not follow one rigid template.

Statement layout A

Account information followed by a standard transaction table.

Statement layout B

Different labels and positioning for the same types of transaction data.

Statement layout C

Another format while the extraction target stays focused on the fields you selected.

Structured outputs

Turn bank statement PDFs into JSON or CSV

Move selected account and transaction data out of the original statement and into a structured format that is easier to review or reuse. If you are working with a larger PDF workflow, the guide on extracting specific data from PDF documents explains the same field-based approach in more detail.

Bank statement to JSON

Use JSON when account and transaction data needs to feed an application, database, API or another structured workflow. 

{
  "account_holder": "Example Company",
  "currency": "EUR",
  "opening_balance": 8240.00,
  "closing_balance": 11290.00,
  "transactions": [
    {
      "date": "2026-08-04",
      "description": "Office Supplies",
      "debit": 180.00
    }
  ]
}

Bank statement to CSV

Export transaction data to CSV for spreadsheet review, reconciliation or another tabular workflow.

DateDescriptionDebitCreditBalance
04/08/2026Office Supplies€180—€8,060
08/08/2026Client Payment—€2,400€10,460
14/08/2026Software€320—€10,140

Bank Statement OCR

Turn statement text into transaction fields you can actually use

Bank statement OCR can read text from scanned or image-based statements. The next challenge is organizing that text into account and transaction data.

Heyyel Data Extractor combines document recognition with field-based extraction so the result can be structured around balances, dates, descriptions, debits, credits and other selected information.

PDF PNG JPG WebP TIFF
1
Bank statement
PDF, scan or image
↓
2
Document recognition
Read statement content and transaction rows
↓
3
Selected statement fields
Account details, balances and transaction values
↓
4
Structured result
JSON or CSV

Bank statement processing

Reduce repetitive transaction entry

When statement data needs to be reviewed, categorized or compared, the same transaction details often have to be copied out manually.

Manual statement processing

1
Open the statement

Locate the account information and transaction table.

2
Copy transaction rows

Enter dates, descriptions, debits and credits elsewhere.

3
Repeat across pages

Continue the same process for the rest of the statement.

With bank statement extraction

1
Choose the fields

Select account information, balances and transaction-level data.

2
Extract structured values

Return the transaction data around the structure you defined.

3
Export the result

Use JSON or CSV for the next step in your workflow.

Bank statement use cases

Structure statement data around the job you need to do

Transaction review

Create a structured view of statement activity without reading every row manually.

  • Transaction date
  • Description
  • Debit
  • Credit
  • Balance

Reconciliation workflows

Export bank statement data to a tabular format for comparison and review.

  • Account reference
  • Transaction amount
  • Transaction reference
  • Counterparty
  • Running balance

Financial data preparation

Add fields that help organize statement data for internal reporting workflows.

  • Statement period
  • Currency
  • Opening balance
  • Closing balance
  • Custom categories

Bank statements rarely exist in isolation inside a finance workflow. If the same process also covers supplier bills or purchase proofs, you can use the same extraction approach for invoices and receipts.

FAQ

Bank statement data extraction questions

Bank statement data extraction identifies account information, balances and transaction details such as dates, descriptions, debits and credits and converts them into structured data.

You can extract fields such as account holder, account number, statement period, currency, opening balance, closing balance and transaction details including dates, descriptions, debits, credits and references.

Yes. Heyyel Data Extractor supports PDF data extraction for bank statements as well as PNG, JPG, WebP and TIFF documents.

Yes. Scanned and image-based bank statements can be processed and selected account and transaction information can be returned as structured fields.

Yes. Extracted bank statement fields and transaction data can be exported to CSV for spreadsheet and review workflows.

Yes. Selected bank statement information can also be returned as structured JSON.

Yes. Suggested fields are editable, and you can add fields such as transaction category, counterparty, internal tag or another value relevant to your workflow.

Heyyel Data Extractor can perform the core task of a bank statement parser by extracting selected account and transaction information into structured fields while allowing you to customize the output structure.

Try it on a bank statement

Turn statement transactions into structured data

Choose the account and transaction fields you need and extract them without entering every row manually.

Extract bank statement data now →
77 languages Editable fields JSON & CSV 1 credit per page