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HumanAIze Hackathon - Fin-Tech Edition

TEAM: CAA AGENTS

Team Members

  • Anushka Mokashi
  • Atharva Todkary
  • Chaitanya Dond

Loan Prediction and Credit Monitoring System

Table of Contents

Introduction

Our credit scoring and loan prediction system uses technologies like AI and machine learning for monitoring and calculating credit scores. It can gives you loan predictions and suggestions for credit management plans to boost your credit score. Our system provide features like credit score monitoring, alerts, predict loan offers and debt management plans to help you improve your credit score. By analyzing the relationship between credit scores and NPAs (Non-Performing Assets), we highlight the significance of keeping a strong credit history.

Features

  • View Credit Score: Predict the credit score of customers.
  • Loan Eligibility Assessment: Determine the eligibility of customers for loans.
  • Credit Score Simulator: Simulate different scenarios to see how they impact credit scores.
  • Real-time credit score monitoring and alerts.: Alerts for overdue loan repayments to customer.
  • Early Warning System: Alerts for overdue loan repayments and potential risks to admin.
  • Admin Dashboard: View all customer payment histories, receive alerts, and manage risks.
  • Customer Dashboard: Receive alerts about installments, view current remaining debts.
  • NPA(Non-Performing Assets) and Credit Score relations: Admin Dashboard recieve alerts about non-performing assets.
  • AI assistant for questionnaire: Ask our AI questions realted to credit score and related topics.
  • Tailored Debt management Plans(Credit Score improvement suggestor): User can use AI assistant for detailed guidance inorder to improve credit score.

Tech Stack

  • Backend: Flask
  • Frontend: React, HTML, JavaScript
  • Database: MongoDB

Installation

  1. Clone the repository: 
    git clone https://github.com/your-username/loan-prediction-system.git
cd loan-prediction-system
  2. Install the dependencies: 
    pip install -r requirements.txt
  3. Install the dependencies: 
    cd frontend
npm i
npm install
npm start
  4. Start the backend server: 
    cd backend
flask run

Contact