aws-samples/rgcn-fraud-detector
RGCN model for real-time fraud detection
This tool helps financial institutions and e-commerce platforms detect fraudulent transactions in real time. It takes in your raw transaction data, including details like card information, transaction amounts, and timestamps, and outputs a probability score for each transaction indicating how likely it is to be fraud. It's designed for data scientists and fraud analysts who need to build and deploy robust fraud detection models.
No commits in the last 6 months.
Use this if you need to build a fraud detection system that identifies suspicious transactions quickly and accurately by leveraging complex relationships within your transaction data.
Not ideal if you don't have detailed, connected transaction data or are looking for a simple, rule-based fraud detection solution.
Stars
11
Forks
3
Language
Jupyter Notebook
License
MIT-0
Category
Last pushed
Jan 27, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/aws-samples/rgcn-fraud-detector"
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
aws-solutions-library-samples/fraud-detection-using-machine-learning
Setup end to end demo architecture for predicting fraud events with Machine Learning using...
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...