payment-fraud

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Open source, self-hosted, multi-agent fraud detection. Real-time XGBoost decisions, drift-aware retraining, plain-language LLM investigations.

ML-powered fraud detection for UPI transactions | 87% F1-Score | XGBoost + Flask | Real-time predictions | Interactive notebooks

🛡️ Stripe邮箱风控检测系统 - 专业级邮箱风险检测工具，模拟Stripe风控逻辑，预测支付成功率，135000+临时邮箱黑名单，支持IPQS专业API

Fraud prevention module for PrestaShop platfom. It help merchants to minimize the payment fraud and therefore improve the revenues.

Real-time blockchain fraud detection using autonomous multi-agent AI swarms. Detect fraud in <2s with 150x faster vector search (HNSW), 84.8% accuracy, and 73% cost reduction. Features ERC-1155 trust scores, MCP integration, and reflexion learning.

This is the complementary repository for "Payment fraud identification by means of business process anomaly detection", the master thesis of Keyvan Amiri Elyasi submitted at the Junior Professorship of Management Analytics, University of Mannheim (July 2022)

End-to-end credit card fraud detection using XGBoost, SMOTE, and Streamlit with 99% recall on 400K+ transactions.

Source-grounded AI agent for vendor payment verification, deterministic fraud controls, human approval, and signed release workflows.

FastAPI phishing-security platform for multi-channel lure scanning, PayShield payment-scam decisions, AI-agent prompt-injection safety, passkey step-up, and STIX/Sigma/TAXII CTI workflows.

Closed-loop GenAI payment fraud red-teaming system: 34-vector attack ontology, 3-layer hybrid simulator, and a 3-layer detection ensemble that co-evolves against its own attacker in an adversarial Arena. Real fidelity metrics, SHAP explainability, and per-vector detection reporting. Built for Mastercard Innovation Challenge 2026.

Official Python client for Kaidn, the fraud and abuse scoring API. Score a signup, login or checkout and get allow/review/block with the reasons. Zero dependencies.

Best fraud prevention solutions, organized by threat and detection layer. Compare fraud detection software and fraud prevention platforms across identity fraud, account takeover, payment fraud, and bots, with guidance on fraud detection and prevention.

Uncertainty-aware AI Risk Manager for payment fraud — behavioral intelligence, decision economics, safe automation, chronological evaluation and Razorpay Test Mode.

A machine learning project to detect payment fraud using features like account age, payment method, and transaction time. Involves data analysis, preprocessing, visualization, and prediction using a Random Forest classifier.

Multi-feed IOC enrichment tool with payment fraud scoring for ACH, Wire, and SWIFT infrastructure

A machine learning project to detect payment fraud using features like account age, payment method, and transaction time. Includes data visualization, preprocessing, and a Random Forest model for prediction.

Official PHP client for Kaidn, the fraud and abuse scoring API. Score a signup, login or checkout and get allow/review/block with the reasons. PHP 7.4+, no Composer dependencies.

Free AI scam detection — check screenshots (fake payment screenshots), messages, links, emails & phone numbers for fraud. Live at scamcheck.asquaresolution.com.

A Machine Learning-based Online Payment Fraud Detection System that identifies fraudulent and legitimate transactions using Logistic Regression, Decision Tree, and Random Forest algorithms. Built with Python, Pandas, NumPy, Scikit-learn, and Matplotlib.