SEPA Credit Transfer Data

This dataset provides granular records of SEPA credit transfers, including validated IBANs, BIC codes, purpose codes, and euro-zone settlement details. It enables comprehensive analysis of cross-border euro transactions, compliance monitoring, and operational insights for financial institutions and regulators.

  • last updated 29 Oct 2025
  • by GoMask
The brief that made it

Transaction monitoring and compliance reporting

Sample rows

preview · 8 of 803 rows · all 23 columns
transaction_idstringstatusstringamount_eurfloatis_intra_eurozonebooleansender_address_countrystringtransaction_datedatetimecurrencystringsender_ibanstringsender_bicstringsender_namestringsender_address_streetstringsender_address_citystringsender_address_postal_codestringreceiver_ibanstringreceiver_bicstringreceiver_namestringreceiver_address_streetstringreceiver_address_citystringreceiver_address_postal_codestringreceiver_address_countrystringpurpose_codestringremittance_informationstringsettlement_datedate
BATCH1A4X9J2VZ6completed125.3trueDE2024-01-03T10:32:13ZEURDE23100100101234567893DEUTDEFFXXXMartina BauerHauptstrasse 12Frankfurt60313ES9121000418450200051332CAIXESBBXXXLuis OrtegaCalle Mayor 8Madrid28013ESOTHRMonthly shared expense2024-01-03
BATCH1B6C5K7P4Q8completed50trueNL2024-01-08T21:22:58ZEURNL91ABNA0417164300ABNANL2AEva de VriesKeizersgracht 22Amsterdam1015CPDE89370400440532013000COBADEFFXXXJonas MöllerLindenstrasse 7Berlin10178DEGIFTBirthday present2024-01-09
BATCH1C1M8N5S2T3completed895trueFR2024-01-14T18:15:00ZEURFR7630006000011234567890189AGRIFRPPXXXCamille DuboisRue de Rivoli 14Paris75001IT60X0542811101000000123456BCITITMMXXXAlessandro RossiVia Roma 21Milan20121ITRENTApartment rent January2024-01-15
BATCH1D3Z6L2V1R7completed20000trueLU2024-01-20T09:05:40ZEURLU280019400644750000BCEELULLXXXLuxInvest AGBoulevard Royal 42Luxembourg2449DE89370400440532013000COBADEFFXXXCommerzbank AGKaiserstrasse 16Frankfurt60311DEINVEInvestment transfer for Q12024-01-22
BATCH1E9Q8X5J3F2completed40.75trueAT2024-01-23T13:59:42ZEURAT611904300234573201BAWVATWWXXXSebastian HuberPraterstrasse 8Vienna1020BE68539007547034KREDBEBBSofie JanssensRue Neuve 18Brussels1000BETRAVTrain ticket reimbursement2024-01-23
BATCH1F7H1S4D9C8completed135000falseCH2024-02-01T11:00:07ZEURCH9300762011623852957CRESCHZZ80ASwissTrade GmbHBahnhofstrasse 55Zurich8001DE89370400440532013000COBADEFFXXXCommerzbank AGKaiserstrasse 16Frankfurt60311DEINTEInternational goods settlement2024-02-02
BATCH1G4K2T7V0S6completed2200trueIE2024-02-07T22:10:50ZEURIE29AIBK93115212345678AIBKIE2DPatrick O'LearySt Stephen's Green 5DublinD02HX65PT50000201231234567890154CGDIPTPLAna MartinsRua Augusta 13Lisbon1100-053PTLOANPersonal loan transfer2024-02-08
BATCH1H1N9L3Q2Z4completed9.99falseFI2024-02-10T02:59:11ZEURFI2112345600000785NDEAFIHHJari VirtanenEsplanadi 4Helsinki00130SE4550000000058398257466ESSESESSEmma KarlssonVasagatan 10Stockholm11120SEGIFTGift for friend2024-02-10

What the 803 rows show

from the 803-row sample
  • 77%is_intra_eurozone = true
  • 180.0median amount_eur
  • 11purpose codes
  • 21receiver address countries
  • 68receiver address cities
  • 69sender address cities
status802 rows by value
038076037pending5%756completed94%8failed1%1cancelled0%
amount_eur802 rows, in bands of 100k
03857707639822900090500k1Mamount_eur →

Median 180.0, from 0.01 to 1,000,000.

sender_address_country794 rows with a value · 9 left blank
  1. DE263
  2. NL62
  3. FR55
  4. IT51
  5. LU45
  6. ES42
  7. BE41
  8. FI39
  9. AT34
  10. IE29
23 columns by typefrom the column list below
  • string 19
  • float 1
  • date 1
  • datetime 1
  • boolean 1

Columns

23 columns in four groups
blueprint · 23 columns
columntypedescriptionexample
Text 19 columns
transaction_idstringUnique identifier for the SEPA credit transfer transactionuniqueBATCH1A4X9J2VZ6
currencystringCurrency code for the transaction, typically EUR for SEPAEUREUR
sender_ibanstringInternational Bank Account Number of the senderDE23100100101234567893
sender_bicstringBank Identifier Code of the sender's bankDEUTDEFFXXX
sender_namestringName of the sender account holderMartina Bauer
sender_address_streetstringStreet address of the senderoptionalHauptstrasse 12
sender_address_citystringCity of the senderoptionalFrankfurt
sender_address_postal_codestringPostal code of the senderoptional60313
sender_address_countrystringCountry code of the sender (ISO 3166-1 alpha-2)optionalDE
receiver_ibanstringInternational Bank Account Number of the receiverES9121000418450200051332
receiver_bicstringBank Identifier Code of the receiver's bankCAIXESBBXXX
receiver_namestringName of the receiver account holderLuis Ortega
receiver_address_streetstringStreet address of the receiveroptionalCalle Mayor 8
receiver_address_citystringCity of the receiveroptionalMadrid
receiver_address_postal_codestringPostal code of the receiveroptional28013
receiver_address_countrystringCountry code of the receiver (ISO 3166-1 alpha-2)optionalES
purpose_codestringSEPA purpose code indicating the reason for the payment11 codes · optionalOTHR
remittance_informationstringUnstructured information or reference provided by the sender for the receiveroptionalMonthly shared expense
statusstringCurrent status of the transaction (e.g., pending, completed, failed)pending · completed · failed · cancelledcompleted
Numbers 1 column
amount_eurfloatAmount of the credit transfer in euros0.01 or more125.3
Dates and times 2 columns
transaction_datedatetimeDate and time when the transaction was initiated2024-01-03T10:32:13Z
settlement_datedateDate when the interbank settlement occurredoptional2024-01-03
True or false 1 column
is_intra_eurozonebooleanIndicates if both sender and receiver banks are in the euro-zonetrue

Use it for

  • is intra euroz…77%614 of 802 rowsmean amount eur by st…14.3kpend…27.3kcomp…27.9fail…127.0canc…

    A finance dashboard

    The is_intra_eurozone rate, amount_eur by status and a breakdown of sender_address_country. Excel, Power BI or Tableau.

  • Why do 614 of 802 rows have is_intra_eurozone = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 803 rows.

  • A software demo

    Believable transactions with transaction_date, amount_eur and currency to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 23 columns, your size and your rules. See 20 rows before you pay.

Preview 20 rows free

1,000 rows: $1.99 · 10,000: $12.99One-time. No subscription. All prices

This dataset803 rows23 columns
Yours1,000 rows23 columnssender_address_street: UK only

blueprint · sepa-credit-transfer-data

Behind this dataset

Same schema. As many rows as you need.

These 803 rows came out of a blueprint — 23 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • End-to-end identification unique
  • IBAN required for all accounts
  • BIC optional within SEPA zone
  • Currency must be EUR
  • XML ISO20022 pain.001 message format
  • Execution date T+1
  • No amount limit for SCT
  • Instant SEPA (SCT Inst) in 10 seconds
Rows
Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
sepa-credit-transfer-data

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