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GrpHdr
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CdtTrfTxInf
dict
{ "MsgId": "MSG123456789-dup0087", "CreDtTm": "2023-04-15T10:30:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456789" }, "PmtTpInf": { "CtgyPurp": "SALA" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 2000 }, "Dbtr": { "Nm": "John Doe" }, "DbtrAcct": { "Id": { "IBAN": "DE89370400440532013000" } }, "DbtrAgt": { "FinInstnId": { "BIC...
{ "MsgId": "MSG123456790-dup0088", "CreDtTm": "2023-04-15T10:35:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456790" }, "PmtTpInf": { "CtgyPurp": "SUPP" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 3000 }, "Dbtr": { "Nm": "Alice Johnson" }, "DbtrAcct": { "Id": { "IBAN": "ES6600190022450687420235" } }, "DbtrAgt": { "FinInstnId": { ...
{ "MsgId": "MSG123456791-dup0089", "CreDtTm": "2023-04-15T11:00:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456791" }, "PmtTpInf": { "CtgyPurp": "INTC" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 500 }, "Dbtr": { "Nm": "Charlie White" }, "DbtrAcct": { "Id": { "IBAN": "DE89370400440532013000" } }, "DbtrAgt": { "FinInstnId": { ...
{ "MsgId": "MSG123456792-dup0090", "CreDtTm": "2023-04-15T11:05:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456792" }, "PmtTpInf": { "CtgyPurp": "CORT" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 1000 }, "Dbtr": { "Nm": "Eve Black" }, "DbtrAcct": { "Id": { "IBAN": "ES6600190022450687420235" } }, "DbtrAgt": { "FinInstnId": { "...
{ "MsgId": "MSG123456793-dup0091", "CreDtTm": "2023-04-15T11:10:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456793" }, "PmtTpInf": { "CtgyPurp": "TREA" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 800 }, "Dbtr": { "Nm": "Grace Red" }, "DbtrAcct": { "Id": { "IBAN": "DE89370400440532013000" } }, "DbtrAgt": { "FinInstnId": { "BIC...
{ "MsgId": "MSG123456794-dup0092", "CreDtTm": "2023-04-15T11:15:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456794" }, "PmtTpInf": { "CtgyPurp": "SALA" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 2500 }, "Dbtr": { "Nm": "Ivy Pink" }, "DbtrAcct": { "Id": { "IBAN": "ES6600190022450687420235" } }, "DbtrAgt": { "FinInstnId": { "B...
{ "MsgId": "MSG123456795-dup0093", "CreDtTm": "2023-04-15T11:20:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456795" }, "PmtTpInf": { "CtgyPurp": "SUPP" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 5000 }, "Dbtr": { "Nm": "Kara Orange" }, "DbtrAcct": { "Id": { "IBAN": "DE89370400440532013000" } }, "DbtrAgt": { "FinInstnId": { "...
{ "MsgId": "MSG123456796-dup0094", "CreDtTm": "2023-04-15T11:25:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456796" }, "PmtTpInf": { "CtgyPurp": "INTC" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 200 }, "Dbtr": { "Nm": "Mia Gray" }, "DbtrAcct": { "Id": { "IBAN": "ES6600190022450687420235" } }, "DbtrAgt": { "FinInstnId": { "BI...
{ "MsgId": "MSG123456797-dup0095", "CreDtTm": "2023-04-15T11:30:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456797" }, "PmtTpInf": { "CtgyPurp": "CORT" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 400 }, "Dbtr": { "Nm": "Olivia Black" }, "DbtrAcct": { "Id": { "IBAN": "DE89370400440532013000" } }, "DbtrAgt": { "FinInstnId": { "...
{ "MsgId": "MSG123456798-dup0096", "CreDtTm": "2023-04-15T11:35:00", "NbOfTxs": 1 }
{ "PmtId": { "EndToEndId": "EETR123456798" }, "PmtTpInf": { "CtgyPurp": "TREA" }, "IntrBkSttlmAmt": { "Ccy": "EUR", "Amt": 600 }, "Dbtr": { "Nm": "Quinn Red" }, "DbtrAcct": { "Id": { "IBAN": "ES6600190022450687420235" } }, "DbtrAgt": { "FinInstnId": { "B...

ISO 20022 100 — Free Sample (10 records)

This is a free 10-record sample of the full 100-record commercial dataset. Every record in this sample is a real, valid bfsi record — real records, just the data. you'd build by hand.

What's in this sample

  • 10 records in records.jsonl (NDJSON, one record per line)
  • Schema-validated: every record parses against the real industry-standard schema before publishing
  • Ready to use: import directly into any bfsi pipeline — no transformation step needed
  • Format: standard JSON Lines (.jsonl), bfsi-native structure

Why these records hold up

Most synthetic datasets are "good enough" — they look like the right shape, but fail against real-world parsers. Cottonwood Development's datasets are generated and validated against the actual schema:

  • Healthcare records validate as valid FHIR R4 Patient resources
  • Banking messages parse against the ISO 20022 pacs.008.001.10 XSD
  • CRM records maintain referential integrity (customer → orders → line items)
  • Invoice records have internally-consistent totals (subtotal + tax = total)

Every record passes schema validation before publishing. If it doesn't parse against the real spec, it doesn't ship.

Sample record

{
 "GrpHdr": {
 "MsgId": "MSG123456789",
 "CreDtTm": "2023-04-15T10:30:00",
 "NbOfTxs": 1
 },
 "CdtTrfTxInf": {
 "PmtId": {
 "EndToEndId": "EETR123456789"
 },
 "PmtTpInf": {
 "CtgyPurp": "SALA"
 },
 "IntrBkSttlmAmt": {
 "Ccy": "EUR",
 "Amt": 2000
 },
 "Dbtr": {
 "Nm": "John Doe"
 },
 "DbtrAcct": {
 "Id": {
 "IBAN": "DE89370400440532013000"
 }
 },
 "DbtrAgt": {
 "FinInstnId": {
 "BIC": "DEUTDEFF"
 }
 },
 "Cdtr": {
 "Nm": "Jane Smith"
 },
 "CdtrAcct": {
 "Id": {
 "IBAN": "GB29NWBK60161331926819"
 }
 },
 "CdtrAgt": {
 "FinInstnId": {
 "BIC": "BNPAFRPP"
 }
 }
 }
}

Schema

The full dataset uses the following field structure:

Field Type Description
GrpHdr.MsgId string Unique message identifier
GrpHdr.CreDtTm datetime ISO 8601 creation timestamp
GrpHdr.NbOfTxs integer Number of transactions (1 per message)
CdtTrfTxInf.PmtId.EndToEndId string End-to-end payment reference
CdtTrfTxInf.PmtTpInf.CtgyPurp string Category purpose code (SALA, INTC, etc.)
CdtTrfTxInf.IntrBkSttlmAmt.Amt decimal Settlement amount
CdtTrfTxInf.IntrBkSttlmAmt.Ccy string ISO 4217 currency code (USD, EUR, GBP, etc.)
CdtTrfTxInf.Dbtr.Nm string Debtor (sender) name
CdtTrfTxInf.DbtrAcct.Id.IBAN string Debtor IBAN
CdtTrfTxInf.Cdtr.Nm string Creditor (receiver) name
CdtTrfTxInf.CdtrAcct.Id.IBAN string Creditor IBAN

Use cases

  • Test fixtures for payment processing systems
  • Demo data for fintech applications
  • ETL pipeline testing — validate payment ingestion
  • Parser development for ISO 20022 implementations
  • ML training for fraud detection, payment categorization

Get the full 100-record commercial dataset

This is a 10-record sample. The full commercial dataset contains 100 records for $25, Schema-validated, with full JSON representations of ISO 20022 pacs.008.001.10 messages.

Buy on Gumroad: https://bluecore8.gumroad.com/l/cottonwood-bfsi-100-records

About Cottonwood

A one-person data shop generating Schema-validated synthetic datasets for AI training, ML eval, and application testing. Every product is generated against an industry-standard schema and validated against the real parser before publishing. 100% synthetic, no real customer data, no legal overhead.

License

This sample is released under CC0 1.0 (public domain dedication). You can use it for any purpose, including commercial use, without attribution.

The full commercial dataset is sold under a separate license (see Gumroad product page for terms).

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