Credit Fraud Detection for the course project for the master's degree in Software and Systems Engineering.

ML-FinFraud-Detector is a machine learning project for detecting financial transaction fraud. Utilizing XGBoost, precision-recall, and ROC curves, it provides accurate fraud detection. Explore feature importance, evaluate model performance, and enhance financial security with this comprehensive fraud detection solution.

Developed and evaluated machine learning and deep learning models for detecting financial fraud.

The Wirecard scandal is considered one of the largest financial scandals of the decade, which caused losses of several billion euros. This analysis examines the digit structure of Wirecard's financial figures in the period from 2005 to 2019 by analyzing the conformity with the expected frequency distributions according to Benford's law. The resu…

Fraud detection using Deep Neural Networks to predict fraudulent transactions in financial data. 🚨🤖 Complete process from EDA and data preprocessing to model training and evaluation. 📊🔍

🛡️ Welcome to our Credit Card Fraud Detection project! 💳 Harnessing the formidable prowess machine learning, we're steadfast in our mission to fortify your financial stronghold against deceitful adversaries. Join our crusade for financial resilience,Ensuring every transaction is securely monitored! 🔐💯

Application built for example financial company that predicts if a transaction is fraudulent. Model trained on sample data from kaggle

ML model developed using European credit card transaction data to identify suspicious activities.