mvram123/Money_Laundering_Detection
Money Laundering Detection Using Machine Learning
This solution helps financial institutions efficiently detect money laundering by reducing false alarms from existing Anti-Money Laundering (AML) systems. It takes transaction data flagged by current rule-based systems and uses machine learning to re-evaluate them, outputting a more accurate classification of 'fraud' or 'not fraud'. Compliance officers, risk analysts, and fraud prevention teams at banks or mobile money services would use this.
No commits in the last 6 months.
Use this if your financial institution struggles with high operational costs due to numerous false positive alerts from your current static rule-based Anti-Money Laundering systems.
Not ideal if you are looking for a complete, end-to-end AML system rather than a tool to enhance an existing one, or if you don't have transaction data to feed into a model.
Stars
59
Forks
20
Language
Python
License
—
Category
Last pushed
Oct 09, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mvram123/Money_Laundering_Detection"
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...