Credit Card Transactions

This dataset provides granular, masked credit card transaction records including transaction amounts, merchant details, timestamps, authorization codes, and fraud flags. It supports robust analysis for fraud detection, merchant risk assessment, and payment trends across regions and card types. The dataset is ideal for financial institutions, payment processors, and analytics teams seeking actionable insights into card-based payments.

  • opened 7 times
  • last updated 29 Oct 2025
  • by GoMask
The brief that made it

Automated fraud detection and prevention

Sample rows

preview · 8 of 206 rows · all 17 columns
transaction_idstringcard_typestringtransaction_amountfloatis_fraudbooleanmerchant_category_descriptionstringmasked_card_numberstringcurrency_codestringtransaction_datetimedatetimemerchant_idstringmerchant_namestringmerchant_category_codestringauthorization_codestringfraud_detection_methodstringtransaction_statusstringentry_modestringterminal_idstringmerchant_countrystring
TRX-001A2D3BVisa48.75falseGrocery Stores******9274USD2024-04-03T10:34:12ZMER-5411AFreshMart Grocery5411XK9V2B6blankapprovedchipTERM-7592US
TRX-001B3F4CMasterCard129.99falseFast Food Restaurants*******1812USD2024-04-03T16:22:41ZMER-5814BBurger Express5814GQ2W7T8blankapprovedswipeTERM-4841US
TRX-001C4H5DVisa2037.5falseElectronics Stores*********3024USD2024-04-03T21:55:09ZMER-5732CTechZone Electronics5732PZ4J2S6blankapprovedchipTERM-1983US
TRX-001D5J6EVisa17.99falseDepartment Stores*********5127USD2024-04-04T12:11:43ZMER-5311DShopSmart Dept5311LQ1M9C8blankapprovedchipTERM-3172US
TRX-001E6K7FVisa5.25falseMiscellaneous General Merchandise*******7426USD2024-04-04T19:45:22ZMER-5399EValueMart5399DJ5T3U1blankapprovedchipTERM-7046US
TRX-001F7L8GMasterCard65falseBook Stores******1839USD2024-04-05T08:26:00ZMER-5942FBooks & Beyond5942MV8Q6B2blankapprovedmanualTERM-6157US
TRX-001G8M9HVisa999999.99falseAutomobile Dealers*********2591USD2024-04-05T23:59:59ZMER-5511GAutoWorld5511TZ6N4V7blankapprovedchipTERM-4401US
TRX-001H9N0IVisa32.4falseFast Food Restaurants*******3981USD2024-04-06T14:20:07ZMER-5814HPizza Point5814QK3D9E5blankapprovedcontactlessTERM-5893US

What the 206 rows show

from the 206-row sample
  • 2%is_fraud = true
  • 151.4median transaction_amount
  • 5transaction statuses
  • 5entry modes
  • 8currency codes
  • 8merchant countries
card_type206 rows by value
065130126Visa61%39Master…19%15Amex7%12Discov…6%14Other7%
transaction_amount206 rows, in bands of 100k
01052102040000000020500k1Mtransaction_amount →

Median 151.4, from 0.01 to 1,000,000.

merchant_category_description206 rows · top 10 of 29 values
  1. Electronics Stores35
  2. Fast Food Restaurants22
  3. Department Stores19
  4. Book Stores17
  5. Grocery Stores13
  6. Auction Houses13
  7. Clothing Stores11
  8. Automobile Dealers10
  9. Grocery Stores, Supermarkets9
  10. Grocery Stores and Supermarkets9
17 columns by typefrom the column list below
  • string 14
  • float 1
  • datetime 1
  • boolean 1

Columns

17 columns in four groups
blueprint · 17 columns
columntypedescriptionexample
Text 14 columns
transaction_idstringUnique identifier for each credit card transactionuniqueTRX-001A2D3B
masked_card_numberstringMasked credit card number (e.g., last 4 digits or partially obscured)******9274
currency_codestringISO 4217 currency code for the transaction (e.g., USD, EUR)8 codesUSD
merchant_idstringUnique identifier for the merchant accepting the paymentMER-5411A
merchant_namestringName of the merchant where the transaction occurredFreshMart Grocery
merchant_category_codestringStandard merchant category code (MCC) indicating the type of merchant5411
merchant_category_descriptionstringHuman-readable description of the merchant categoryoptionalGrocery Stores
authorization_codestringCode provided by the payment processor authorizing the transactionXK9V2B6
fraud_detection_methodstringMethod or system used to detect fraud for this transaction (e.g., rule-based, ML model)2 methods · optionalrule-based
card_typestringType of credit card used (e.g., Visa, MasterCard, Amex)Visa · MasterCard · Amex · Discover · Other · optionalVisa
transaction_statusstringStatus of the transaction (e.g., approved, declined, pending)approved · declined · pending · reversed · cancelledapproved
entry_modestringHow the card was entered (e.g., chip, swipe, contactless, manual)chip · swipe · contactless · manual · online · optionalchip
terminal_idstringIdentifier for the payment terminal used for the transactionoptionalTERM-7592
merchant_countrystringCountry code (ISO 3166-1 alpha-2) where the merchant is located8 countriesUS
Numbers 1 column
transaction_amountfloatTotal amount of the transaction in the local currency0.01 or more48.75
Dates and times 1 column
transaction_datetimedatetimeDate and time when the transaction occurred2024-04-03T10:34:12Z
True or false 1 column
is_fraudbooleanFlag indicating whether the transaction is suspected or confirmed as fraudulentfalse

Use it for

  • is fraud2%5 of 206 rowsmean transaction amou…17.7kVisa671.8Mast…6.3kAmex550.5Disc…

    A finance dashboard

    The is_fraud rate, transaction_amount by card_type and a breakdown of merchant_category_description. Excel, Power BI or Tableau.

  • Why do 5 of 206 rows have is_fraud = true?

    A class exercise

    Hand out the rows and one question. Everyone works from the same 206 rows.

  • A software demo

    Believable transactions with masked_card_number, transaction_amount and currency_code to fill a screen in front of a buyer.

Not quite right?

Make it yours.

Same 17 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 dataset206 rows17 columns
Yours1,000 rows17 columnsmerchant_country: UK only

blueprint · credit-card-transactions

Behind this dataset

Same schema. As many rows as you need.

These 206 rows came out of a blueprint — 17 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
  • Card numbers masked except last 4 digits
  • Transaction amount has realistic distribution
  • Merchant category codes are valid
  • Authorization code format matches standard
  • Fraud score 0-100 based on patterns
Rows
Open the blueprint in Data Factory

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

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