Scholarship-Policy-Compliance-Bot

🛡️ Scholarship Policy Compliance Bot

A Hybrid AI System for detecting scholarship fraud and enforcing dual-benefit policies in real-time.

📸 Demo Dashboard

📌 Problem Statement

Educational institutions face massive fund leakage due to:

1. Dual Benefit Violations: Students applying for conflicting scholarships (Double Dipping).
2. Fraud: Fake income certificates or data anomalies.
3. Manual Errors: Human verification is slow and error-prone.

💡 The Solution: Hybrid AI Architecture

We solved this using a two-layer approach, combining deterministic logic with machine learning.

Component	Technology	Purpose
Policy Engine	Python (Pandas)	Enforces strict government rules (GPA cuts, Income caps, Mutual Exclusivity) with 100% accuracy.
Fraud Guard	Scikit-Learn	An Isolation Forest model (Unsupervised Learning) detects statistical anomalies in applicant data.
Dashboard	Streamlit	Real-time interface for administrators to validate applications.

🚀 Features

• Dynamic Rule Loading: Reads policy rules from Excel/JSON, allowing updates without changing code.
• Dual-Benefit Detection: checks dual_benefit_rules.xlsx to prevent students from holding conflicting grants.
• Anomaly Scoring: Flags “High Risk” applications where Income/CGPA ratios deviate from the norm.
• Explainable AI: Provides exact reasons for rejection (e.g., “Rule DBR-001 Violation”).

🛠️ Installation & Run

1. Clone the repository

   ```bash git clone https://github.com/Arkz-Deepak/Scholarship-Policy-Compliance-Bot.git cd Scholarship-Policy-Compliance-Bot# 🛡️ Scholarship Policy Compliance Bot

2.Install Dependencies bash pip install pandas streamlit scikit-learn openpyxl

3.Run the App bash streamlit run app.py

📂 Project Structure

├── app.py                # Main Dashboard Interface
├── data_loader.py        # Dynamic Data Ingestion Script
├── rules_engine.py       # Deterministic Logic (The "Lawyer")
├── fraud_guard.py        # ML Model (The "Detective")
├── Scholarship dataset/  # Excel/JSON Data Sources
│   ├── students.xlsx
│   ├── scholarships.xlsx
│   ├── dual_benefit_rules.xlsx
│   └── fraud_rules.json
└── README.md             # Documentation

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👥 Team Arkz

Deepak R - AI Architect & Backend Logic

Kamalesh - Frontend & Presentation

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Built for the Build-a-Bot Hackathon 2026.