README.md

metadata

title: Credit Card Fraud Detection
emoji: 📊
colorFrom: red
colorTo: indigo
sdk: gradio
sdk_version: 5.33.1
app_file: app.py
pinned: true
tags:
  - agent-demo-track
  - python
short_description: Explainable & transparent AI credit card fraud detection

AI-Powered Fraud Detection Agent

agent-demo-track Track: 3. Agentic Demo Showcase
Built For: Hugging Face Hackathon - Multimodal Challenge Playground (MCP)
Team: Osama Elmahdy, Muhammed Hisham

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Overview

This Gradio-based AI Agent helps merchants, analysts, and fraud teams assess transaction legitimacy by combining a fraud detection model with reasoning capabilities powered by Hugging Face’s Nemotron-Research-Reasoning-Qwen-1.5B-GGUF model.

Users input transaction details, and the system:

1. Classifies the transaction as fraudulent or not.
2. Uses LLM reasoning to explain the decision and provide recommendations for next steps (e.g., flag, approve, monitor).

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AI Stack

Core Idea

First, check if a transaction is likely fraudulent using a traditional ML model trained on real-world features. Then, invoke an open LLM agent (via GGUF + llama-cpp) to explain and suggest human-friendly actions.

Components Used

• Fraud Detection:
  • Custom-trained classifier (scikit-learn + LIME explanations)
• Reasoning & Recommendations:
  • Hugging Face’s Nemotron-Research-Reasoning-Qwen-1.5B-GGUF running locally via llama-cpp-python
• UI:
  • Gradio

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