jube-home/aml-fraud-transaction-monitoring
Open source AML and Fraud Detection using Machine Learning for Real-Time Transaction Monitoring
This platform helps financial institutions and fintechs monitor financial transactions in real-time to detect and prevent financial crime. It takes transaction data and applies machine learning models and rule-based checks to identify suspicious activity, producing risk scores and automatically generating cases for compliance teams to investigate. It's designed for compliance officers, fraud analysts, and operations managers at banks, fintechs, and other financial service providers.
Use this if you need an open-source, auditable system to monitor high volumes of financial transactions in real-time for both anti-money laundering (AML) and fraud detection, requiring integrated case management.
Not ideal if you are looking for a simple, out-of-the-box solution without the need for customization or the overhead of managing an open-source platform, or if your primary need is not real-time transaction monitoring.
Stars
59
Forks
14
Language
C#
License
AGPL-3.0
Category
Last pushed
Mar 08, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jube-home/aml-fraud-transaction-monitoring"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
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.
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...
Fraud-Detection-Handbook/fraud-detection-handbook
Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook