lmriccardo/fraudolent-transaction-classification
Project for the Big Data Computing course at the University of "La Sapienza" in Master in Computer Science A.A. 2021/2022
This project helps financial institutions and payment processors automatically identify potentially fraudulent credit card transactions. By analyzing transaction details like amount, card information, and customer identity data, it flags suspicious activity. Risk analysts and fraud detection teams would use this to prioritize investigations and reduce financial losses.
No commits in the last 6 months.
Use this if you need to build or evaluate machine learning models for detecting credit card fraud from a dataset containing various transaction and identity features.
Not ideal if you need a real-time, production-ready fraud detection system out-of-the-box without further development and integration.
Stars
7
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Jun 28, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lmriccardo/fraudolent-transaction-classification"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GoogleCloudPlatform/fraudfinder
Fraudfinder: A comprehensive lab series on how to build a real-time fraud detection system on...
benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
jube-home/aml-fraud-transaction-monitoring
Open source AML and Fraud Detection using Machine Learning for Real-Time Transaction Monitoring
safe-graph/DGFraud
A Deep Graph-based Toolbox for Fraud Detection
curiousily/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for...