Datasets:
metadata
license: apache-2.0
task_categories:
- tabular-classification
tags:
- nigeria
- banking
- finance
- fraud-detection
- synthetic
- african-data
language:
- en
size_categories:
- 1M<n<10M
NIP (Nigeria Inter-Bank Payment) Transfers
Dataset Description
Nigerian Inter-Bank Payment (NIP) transfers with fraud labels
This is a production-grade synthetic dataset with authentic Nigerian banking context, designed for fraud detection, payment anomaly detection, and real-time transaction monitoring.
Key Features
- π³π¬ Nigerian Context: Real bank names, states, demographics
- π ML-Ready Labels: Fraud flag (1.0% prevalence)
- β‘ Large Scale: 3,000,000 rows
- π― Realistic Distributions: Lognormal amounts, temporal patterns, cross-bank transfers
- π Temporal Coverage: 2023-01-01 to 2024-12-31
Dataset Structure
Splits
- Train: 2,100,000 rows (70%)
- Validation: 450,000 rows (15%)
- Test: 450,000 rows (15%)
Schema
Key columns: transfer_id, timestamp, sender/beneficiary accounts & banks, amount_ngn, transfer_type, state, session_id, status, response_time_ms, fraud_flag
Usage
from datasets import load_dataset
# Load full dataset
dataset = load_dataset("electricsheepafrica/nigerian_nip_transfers")
# Load specific split
train_data = load_dataset("electricsheepafrica/nigerian_nip_transfers", split="train")
Labels
- Type: Fraud flag (1.0% prevalence)
- Use Case: fraud detection, payment anomaly detection, and real-time transaction monitoring
Nigerian Context
Includes 14 Nigerian banks (Access, GTBank, UBA, Zenith, etc.), 37 states with population weighting, and authentic NIP transfer patterns including P2P, business, and salary transfers.
Citation
@dataset{nigerian_banking_nip_transfers,
title = {Nigerian NIP (Nigeria Inter-Bank Payment) Transfers},
author = {Electric Sheep Africa},
year = {2025},
publisher = {Hugging Face},
howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/nigerian_nip_transfers}}
}
License
Apache 2.0 - Free for commercial and research use.
Contact
- Organization: Electric Sheep Africa
- Collection: Nigeria Banking & Finance Datasets