A UI tool to review potentially fraudulent transactions and perform operations on them

FraudLabs Pro Fraud Prevention plugin that screen the order transaction for online frauds. Fraud Prevention extension for Magento 1.

This repository contains the implementation of Self organising maps for fraud detection.

https://trustswiftly.com - Identity Verifications (PHP SDK)

Data Engineering Infrastructure Terraform is used to automate the provisioning and management for fintech applications, with a focus on fraud detection.

Fraud Detection Web App for Arbitrum Transactions

Python wrapper for Greip API

Exploratory Data Analysis on Banking Data

A multi-SQL project to detect potential scam traffic on your VoIP network.

This project serves as a simplified illustration of the principles underpinning anti-fraud systems within the financial sector. In this endeavor, we focus on a system featuring an enhanced role model, a suite of REST endpoints responsible for user interaction, and an internal transaction validation logic grounded in a set of heuristic rules.

Developing a robust fraud detection system for financial transactions, identify potential fraudulent activities in real-time, minimizing losses and protecting customer transactions. Conducting comprehensive data preprocessing and feature engineering on transaction data, applying logistic regression, decision trees, and XGBoost.

Predictive modeling projects developed during the Risk & Fraud Analytics course (Master in Business Analytics & Big Data) at IE HST.

Utilize autoencoders for anomaly detection and customer credit risk evaluation

Scam-fraud mail analysis and prevention

Simple project created to suggest how Python could be used to assist new fraud investigators in making decisions during complex investigations. It was my first interaction with Python while attending a Cybersecurity master.

Save From Frauds is a comprehensive application designed to track and report fraudulent entities (e.g., phone numbers, emails, websites) and their associated impacts. Users can log detailed reports describing the nature of the fraud, its impact (financial, emotional, reputational, etc.), and preventive measures to avoid similar scams.

Complete Fraud Protection Checklist

Projeto que engloba soluções de Analitycs para empresas do mercado financeiro. Neste projeto envolvemos problemas de Fraud Detection, Churn Detection e Credit Score.

Predict the probability that a customer does not pay back their credit card balance amount in the future based on their monthly customer profile.

Heavily imbalanced credit dataset was resampled, six machine learning models were fit to training data to predict credit risk. A suggestion was made based on the accuracy of predictions from each model.