fraud-detection-system

This is an Online Transaction Fraud Detection System (FDS) to detect payment frauds. Made using Django.

This repository outlines various solutions using AWS Cloud's AIML services to detect fraud faster.

A machine learning-based fraud detection system that analyzes transaction patterns to identify potentially fraudulent activities. Features a Streamlit web interface for real-time predictions. Note: Model is currently in development with ongoing improvements planned.

Real-time AML transaction scoring pipeline on AWS: Lambda, S3, DynamoDB, SNS, IAM Roles and Terraform (IaC)

AI-powered behavioural fraud detection system for UPI transactions using FastAPI and Streamlit.

Fraud investigation tutorial across 9 phases — same 6 cases, progressively adding LangGraph, tools, HITL, multi-agent coordination, and LangSmith observability

AI-powered deepfake detection system using Deep Learning and Computer Vision to identify manipulated facial images and videos with high accuracy.

Fraud Detection REST API project built with FastAPI and LightGBM Binary Classifier.

Clerivon AI lab/pilot: multi-agent BFSI fraud detection (Monitor→Investigator→Adjudicator→Explainer→Feedback). Synthetic E2E demo — Streamlit, harness, SQLite/Postgres, Docker.

Adversarial evasion attacks on fraud detection models — finding that predictive accuracy doesn't predict robustness (XGBoost, PyTorch, CUDA).

AI Deepfake and Fraud Detection

End-to-end fraud detection — JAX neural nets from scratch, multi-objective Optuna (Pareto recall vs precision), custom Precision@K/Recall@K/Lift@K metrics, SHAP explainability, and GitHub Actions CI/CD. No ML framework shortcuts.

Real-time transaction risk monitoring system with rule-based fraud detection, REST API, and a React dashboard. Built with Node.js, Express, and SQLite.

We address the 'Resilience Gap' in modern autonomous systems. As enterprises transition from AI tools to Agentic AI, the risk of operational drift and systemic capture increases exponentially. Our mission is to provide the Cohesion Layer necessary for secure, sovereign execution.

Generative AI-powered financial fraud detection system built with Google AI Studio and Gemini API.

data-engineering aws pyspark fraud-detection data-pipeline etl-pipeline aws-glue data-lake medallion-architecture banking-analytics

Full-stack Flask insurance workflow system with policy management, QR verification, Twilio SMS alerts, NLP sentiment analysis, and Decision Tree-based fraud detection (77% accuracy).

A high-speed candidate ranking platform and recruiter workspace that solves resume fraud and inaccurate skill matching through automated timeline verification and a semantic knowledge graph.

Open-source bank fraud detection and AML microservice built in Go for transaction monitoring, risk scoring, rule evaluation, and suspicious activity detection.

Real-time fraud detection system with rule-based risk scoring, event streaming, and analytics dashboard. Spring Boot • React • Kafka • Redis • PostgreSQL