electricsheepafrica/africa-synth-banking-atm-network-nigeria

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

ATM Network Transactions

Dataset Description

Nigerian ATM transactions and terminal data with fraud labels

This is a production-grade synthetic dataset with authentic Nigerian banking context, designed for ATM fraud detection, card skimming detection, and network monitoring.

Key Features

• 🇳🇬 Nigerian Context: Real bank names, states, demographics
• 📊 ML-Ready Labels: Fraud flag (1.5% prevalence)
• ⚡ Large Scale: 2,000,000 rows
• 🎯 Realistic Distributions: Lognormal withdrawal amounts, hourly patterns, card/issuer relationships
• 📅 Temporal Coverage: 2023-01-01 to 2024-12-31

Dataset Structure

Splits

• Train: 1,400,000 rows (70%)
• Validation: 300,000 rows (15%)
• Test: 300,000 rows (15%)

Schema

Key columns: transaction_id, timestamp, masked card_number, account_id, card_issuer, atm_owner, terminal_id, transaction_type, amount_ngn, state, dispense_status, response_code, fraud_flag

Usage

from datasets import load_dataset

# Load full dataset
dataset = load_dataset("electricsheepafrica/nigerian_atm_network")

# Load specific split
train_data = load_dataset("electricsheepafrica/nigerian_atm_network", split="train")

Labels

• Type: Fraud flag (1.5% prevalence)
• Use Case: ATM fraud detection, card skimming detection, and network monitoring

Nigerian Context

Real Nigerian bank ATM networks, geographic distribution across 37 states, typical withdrawal patterns, and authentic fraud scenarios including card skimming and testing.

Citation

@dataset{nigerian_banking_atm_network,
  title = {Nigerian ATM Network Transactions},
  author = {Electric Sheep Africa},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/nigerian_atm_network}}
}

License

Apache 2.0 - Free for commercial and research use.

Contact

• Organization: Electric Sheep Africa
• Collection: Nigeria Banking & Finance Datasets