Datasets:
File size: 3,121 Bytes
616d2b4 f8474ac 5ff54bd f8474ac 5ff54bd 5f79856 5ff54bd f8474ac 5ff54bd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | ---
license: other
task_categories:
- tabular-classification
language:
- en
tags:
- fraud
- fraud-detection
- finance
- synthetic
- tabular
- transactions
size_categories:
- 10M<n<100M
---
# Zia Data Labs
## About Zia Data Labs
We believe great data shouldn't cost a fortune or come with strings attached.
At Zia Data Labs we do one thing — produce quality datasets and offer them at prices that make sense. No games. No gatekeeping. Just clean, production-grade data you can trust.
This dataset is completely free. No catch. It's our way of introducing ourselves and letting our work speak for itself.
We love what we do — and we'd love to earn your business.
Come find us. More is coming.
*— The Zia Data Labs Team*
---
## ⚠️ Important Notice
This dataset is the exclusive property of Zia Data Labs. By downloading or using this dataset you agree that it is free to use for personal and professional research, model training, and experimentation. Redistribution, repackaging, and resale are strictly prohibited. Attribution to Zia Data Labs is required in any published work.
---
## Fraud Detection Dataset
A production-grade, large-scale dataset containing 50 million transactions designed to serve both the beginner data scientist and the enterprise data engineer.
What is inside:
- 50 million rows of high-fidelity synthetic transaction data
- 19 carefully engineered fields covering core transaction data, velocity signals, geospatial context, device fingerprinting, and diagnostic fraud labels
- A realistic 2.5% fraud rate simulating the exact needle in a haystack challenge faced by real fraud teams at major financial institutions
- Granular fraud_type labels enabling multi-class classification, not just binary detection
File formats provided:
- sample_50rows.csv — No gate. Inspect immediately.
- fraud_detection_50M.parquet — Full 50 million row file. No gate. Free access.
Quick load example:
import pandas as pd
df = pd.read_parquet('fraud_detection_50M.parquet')
print(df.head())
Schema Overview:
| Block | Fields |
|---|---|
| Core | transaction_id, timestamp, user_id, amount, merchant_id, merchant_category, location_country, payment_method, is_fraud |
| Velocity & Context | ip_address, device_id, user_age_days, is_first_transaction, time_since_last_txn, auth_result |
| Diagnostic | fraud_type |
| Metadata | currency_code, card_network |
| Branding | data_source |
---
## Our New Home
Visit our official new home where our full portfolio of datasets lives and grows:
Zia-Data-Labs on Hugging Face
https://huggingface.co/Zia-Data-Labs
---
## Contact
zia.data.team@protonmail.com
---
## License & Usage
**Zia Data Labs Open Use License**
This dataset is the exclusive property of Zia Data Labs. It is made freely available for personal research, academic and educational use, and model training and development.
It is strictly prohibited to redistribute, repackage, resell, or commercially exploit this dataset in any form. Removing or altering Zia Data Labs attribution is strictly prohibited.
© 2026 Zia Data Labs — All Rights Reserved |