---
title: Fraud Detection Multi-Model
emoji: 🛡️
colorFrom: red
colorTo: blue
sdk: streamlit
sdk_version: 1.57.0
app_file: app.py
pinned: true
suggested_hardware: cpu-basic
python_version: 3.11
---

# Fraud Detection — Multi-Model Live Monitor

Real-time transaction fraud detection using a 3-layer ensemble pipeline.

## Architecture

```
Transaction
    │
    ▼
Layer 1 — Hard Rules
    │  Rule 1: Accessibility + Remote App → Block immediately
    │  Rule 2: Hesitation > 45s + New recipient → bias score ≥ 0.6
    │
    ▼
Layer 2 — Ensemble Scoring
    │  Model A (Sender Behavioral): LightGBM / XGBoost
    │  Model B (Payee Risk Profile): LightGBM
    │  final_score = 0.3 × prob_a + 0.7 × prob_b
    │
    ▼
Layer 3 — Threshold Decision
       score ≥ 0.80  →  Block
       score ≥ 0.50  →  Alert + OTP
       score < 0.50  →  Pass
```

## Files required

| File | Purpose |
|------|---------|
| `model_a_pipeline.joblib` | Sender behavioral model |
| `model_b_pipeline.joblib` | Payee risk profile model |
| `config.json` | Feature list, weights, thresholds |
| `payee_profile_store.csv` | Historical payee lookup table |

## GitHub

[Fraud-Detection-Multi-Model](https://github.com/PlamGG/Fraud-Detection-Multi-Model-)