A Deployment-Derived Online Banking Fraud Detection Inference-Log Dataset from a Live Cloud-Based Deep Learning System

Published: 14 August 2026| Version 1 | DOI: 10.17632/s83xr4fsv9.1
Contributors:
,

Description

This dataset contains 56,962 transaction inference logs collected through a live, cloud-deployed online banking fraud detection demonstration system over a 30-day period in January 2026. The data were gathered through a REST API endpoint hosted on a Ubuntu Linux virtual private server, where a trained hybrid CNN-LSTM model processed each incoming transaction in real time. The dataset contains 98 confirmed fraudulent transactions (0.172% fraud rate). Each record includes 30 input features alongside model-generated outputs comprising fraud probability score, risk level, confidence estimate, action recommendation (BLOCK or ALLOW), and response latency in milliseconds. The deployment was a proof-of-concept system operating as a public demonstration interface and not a licensed banking institution.

Files

Steps to reproduce

Data was collected from a live cloud-based REST API serving a hybrid CNN-BiLSTM fraud detection model over a 30-day period.

Institutions

Categories

Computer Science, Artificial Intelligence, Information Systems Management

Licence