minFraud PHP API

Fraud Detection with unsupervised Clustering

Train different models to detect card transaction fraud effectively, and present the fraud detection rate and KS of the best methods by every % of records.

Credit card fraud detection using Python

Collab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend. About Colab implementation for Fraud Detection in Graph Neural Networks, based on Deep Graph Library (DGL) and PyTorch backend.

This repository contains machine learning tasks for TechnoHacks Internship Program 2023

Real-time fraud detection system for financial transactions using Change Data Capture (CDC), Apache Kafka, Debezium, MySQL, and Spring Boot. Monitors user activity across locations to identify suspicious patterns and block fraudulent accounts.

Contains 4 projects that were implemented during my Creating AI Enabled Systems class as part of my M.S. degree at JHU

In this notebook we take a look at a relevant project that is frequently encountered by insurers: Fraud Detection. For this purpose we use a car data set from a public source and will show the necessary steps to establish an automated fraud detection.

An end-to-end machine learning project to detect credit fraud using XGBoost.

End-to-end fraud detection pipeline using machine learning. Integrated with Slack & email alerts for real-time fraud notifications.

A machine learning project to detect fraudulent credit card transactions using data analysis and classification models.

Racernix is a real-time fraud detection system built with a hybrid engine using Python for machine learning and Rust for high-performance computation. It’s designed to swiftly identify and prevent fraudulent transactions, ensuring security while integrating seamlessly with your future backend.

Fraud-Shield ML model

A concise Streamlit dashboard for analysing transaction data and predicting fraud.

A machine learning-based web application to detect financial fraud in real time. Users can input transaction details and get instant fraud predictions.