| --- |
| license: cc-by-nc-4.0 |
| task_categories: |
| - tabular-classification |
| - time-series-forecasting |
| language: |
| - en |
| tags: |
| - synthetic-data |
| - finance |
| - transactions |
| - banking |
| - fintech |
| size_categories: |
| - 10M<n<100M |
| --- |
| |
| # FreeSyntheticFinancialTransactions50M |
|
|
| A free dataset of 50 million fully synthetic banking transactions, built for developers and researchers who need realistic financial ledger data at scale — for testing banking apps, ledger and reconciliation logic, budgeting and personal-finance tools, or transaction-processing pipelines. No real people, accounts, or transactions are represented in this data. |
|
|
| ## Schema |
|
|
| | Column | Type | Description | |
| |---|---|---| |
| | transaction_id | string | Unique transaction identifier | |
| | account_id | string | Synthetic account identifier | |
| | transaction_type | string | debit, credit, transfer, fee, interest, refund, withdrawal, deposit | |
| | amount | float | Transaction amount | |
| | currency | string | Currency code (USD, EUR, GBP, CAD, AUD, JPY) | |
| | merchant_category | string | Spending category (groceries, dining, utilities, etc.) | |
| | balance_after | float | Running account balance after the transaction | |
| | transaction_timestamp | string | Transaction time (YYYY-MM-DD HH:MM:SS) | |
| | status | string | completed, pending, failed, or reversed | |
|
|
| ## Format |
|
|
| Single Parquet file, Snappy compression, ~1.5 GB, 50,000,000 rows. |
|
|
| ## Quick Start |
|
|
| **pandas** |
| ```python |
| import pandas as pd |
| df = pd.read_parquet("transactions_50M.parquet") |
| ``` |
|
|
| **datasets** |
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("ziadatalabs/FreeSyntheticFinancialTransactions50M") |
| ``` |
|
|
| **duckdb** |
| ```python |
| import duckdb |
| duckdb.sql("SELECT * FROM 'transactions_50M.parquet' LIMIT 10").show() |
| ``` |
|
|
| ## Notes |
|
|
| Each account carries a running balance that updates consistently across its completed transactions, so the ledger stays internally coherent for reconciliation testing. Amounts follow a realistic log-normal distribution (mostly small, occasional large), transaction types and statuses follow typical banking proportions, and most transactions are completed with small tails of pending, failed, and reversed. All entirely synthetic. |
|
|
| ## License & Usage |
|
|
| Released under CC BY-NC 4.0 — personal, research, and educational use permitted, attribution required, no commercial use. |
|
|
| --- |
|
|
| Created by Zia Data Labs. Questions or feedback: zia.data.team@protonmail.com |
|
|
