Datasets:
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
import pandas as pd
df = pd.read_parquet("transactions_50M.parquet")
datasets
from datasets import load_dataset
ds = load_dataset("ziadatalabs/FreeSyntheticFinancialTransactions50M")
duckdb
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