electricsheepafrica/africa-synth-banking-pos-merchants-nigeria

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

POS Merchants & Terminals Registry

Dataset Description

Nigerian POS merchants and terminals registry with fraud labels

This is a production-grade synthetic dataset with authentic Nigerian banking context, designed for merchant fraud detection, POS network optimization, and terminal risk scoring.

Key Features

• 🇳🇬 Nigerian Context: Real bank names, states, demographics
• 📊 ML-Ready Labels: Fraud flag (2.0% prevalence)
• ⚡ Large Scale: 2,000,000 rows
• 🎯 Realistic Distributions: Lognormal monthly volumes, Poisson transaction counts, merchant type distributions
• 📅 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: merchant_id, terminal_id, business_name, merchant_category, state, monthly_volume_ngn, monthly_transactions, registration_date, fraud_flag

Usage

from datasets import load_dataset

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

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

Labels

• Type: Fraud flag (2.0% prevalence)
• Use Case: merchant fraud detection, POS network optimization, and terminal risk scoring

Nigerian Context

Nigerian POS merchant ecosystem, business categories (retail, food, services, transport), state distributions, typical transaction volumes, and fraud patterns including POS swap and cloning.

Citation

@dataset{nigerian_banking_pos_merchants,
  title = {Nigerian POS Merchants & Terminals Registry},
  author = {Electric Sheep Africa},
  year = {2025},
  publisher = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/nigerian_pos_merchants}}
}

License

Apache 2.0 - Free for commercial and research use.

Contact

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