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🏦 Loan Application Management System

A comprehensive end-to-end loan application processing system with automated KYC verification, legal compliance checks, loan eligibility assessment, and dashboard analytics.

📋 Table of Contents

✨ Features

Core Functionality

  • Complete Loan Application Workflow: End-to-end processing from submission to final decision
  • Multi-Stage Verification:
    • ✅ KYC (Know Your Customer) Verification
    • ✅ Legal Compliance Checks
    • ✅ Loan Eligibility Assessment
  • Automated Decision Making: Based on configurable business rules
  • Notification System: Email and alert notifications (simulated in POC)
  • Dashboard Analytics: Comprehensive analytics and reporting

Dashboard Features

  • Regional distribution (APAC, EMEA, AMERICAS, MEA)
  • Country-wise application breakdown
  • Verification stage statistics
  • Financial metrics and trends
  • Timeline analysis

Additional Features

  • User registration and authentication
  • Stock market data integration (existing functionality maintained)
  • RESTful API with CORS support
  • PostgreSQL database with Node.js ORM/helpers
  • Docker containerization

🏗️ System Architecture

┌─────────────┐
│   Client    │
└──────┬──────┘
       │
       ↓
┌─────────────────────────────────────────────────────────┐
│              Node.js / Express Application              │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐ │
│  │    User      │  │    Loan      │  │  Dashboard   │ │
│  │ Management   │  │ Application  │  │  Analytics   │ │
│  └──────────────┘  └──────────────┘  └──────────────┘ │
│                                                         │
├─────────────────────────────────────────────────────────┤
│           Verification Service (Business Logic)         │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  ┌──────────┐  ┌────────────┐  ┌──────────────┐       │
│  │   KYC    │→ │ Compliance │→ │ Eligibility  │       │
│  │  Check   │  │   Check    │  │    Check     │       │
│  └──────────┘  └────────────┘  └──────────────┘       │
│                         ↓                               │
│                  ┌─────────────┐                        │
│                  │   Final     │                        │
│                  │  Decision   │                        │
│                  └─────────────┘                        │
│                         ↓                               │
│                  ┌─────────────┐                        │
│                  │Notification │                        │
│                  └─────────────┘                        │
├─────────────────────────────────────────────────────────┤
│              Node.js Services & PostgreSQL DB           │
└─────────────────────────────────────────────────────────┘

🛠️ Tech Stack

  • Backend: Node.js 20 + Express 4
  • Database: PostgreSQL (via pg)
  • Containerization: Docker & Docker Compose
  • Message Queue: Kafka (optional, infrastructure ready)
  • Additional Libraries:
    • cors for CORS handling
    • bcryptjs for password hashing
    • uuid for application IDs

🚀 Quick Start

Prerequisites

  • Docker and Docker Compose installed (optional)
  • Node.js 20+ and npm

Using Docker

  1. Build and start the application:

    docker compose up --build

  2. The application will be available at:

    • API: http://localhost:5003
    • Health check: http://localhost:5003/

  3. Reseed sample data (optional):

    docker exec -it loan-backend npm run seed:loans

Local Development

  1. Configure environment:

    cp .env.example .env  # set PGHOST, PGUSER, etc.

  2. Install dependencies:

    npm install

  3. Seed baseline data:

    npm run seed:stocks     # Load stock quotes from CSV
node seedLoanData.js 50 # Generate 50 sample loan applications

  4. Run the Node server:

    npm start

Auto-Seeding (optional)

  • Copy .env.example to .env and set your PostgreSQL credentials.
  • Set AUTO_SEED=true if you want the server to seed stocks and IN_MEMORY_LOAN_COUNT (defaults to 25) loan applications automatically on startup.
  • Example: 
    AUTO_SEED=true npm start
    Disable AUTO_SEED for normal production usage.

📊 Workflow Overview

Loan Application Process

The system processes each application through the following stages:

  1. KYC Verification → 2. Compliance Check → 3. Eligibility Assessment → 4. Final Decision → 5. Notification

Each stage can result in APPROVED or REJECTED status. If any stage is rejected, the entire application is rejected.

Verification Criteria

KYC Verification:

  • Email format validation
  • Phone number validation (≥10 digits)
  • Document upload verification
  • Name validation (≥3 characters)
  • Region/country validation

Legal Compliance:

  • Political connections screening
  • Senior employee relative detection
  • Sanctions list screening
  • High-risk country assessment
  • High-value transaction flagging (>$500K)

Loan Eligibility:

  • Debt-to-Income ratio < 40%
  • Credit Score ≥ 650
  • Income ≥ 3x loan amount
  • Maximum loan: $1,000,000
  • Minimum income: $30,000

📖 API Documentation

Key Endpoints

Submit Loan Application:

POST /loan-application/submit
Content-Type: application/json

{
  "name": "John Doe",
  "email": "john.doe@example.com",
  "phone": "+1234567890",
  "region": "AMERICAS",
  "country": "United States",
  "income": 85000,
  "debt": 25000,
  "credit_score": 720,
  "loan_amount": 250000,
  "loan_purpose": "Home Purchase"
}

Check Status:

GET /loan-application/status/{application_id}

Dashboard Analytics:

GET /dashboard/overview
GET /dashboard/by-region
GET /dashboard/by-country
GET /dashboard/verification-stats
GET /dashboard/financial-metrics
GET /dashboard/timeline?days=30

For complete API documentation, see API_DOCUMENTATION.md

📊 Dashboard Analytics

The system provides comprehensive analytics:

  • Overview: Total applications, approval/rejection rates
  • Regional Distribution: Applications by APAC, EMEA, AMERICAS, MEA
  • Country Analysis: Country-wise breakdown with approval rates
  • Verification Funnel: Pass rates at each verification stage
  • Financial Metrics: Average credit scores, DTI ratios, loan amounts
  • Timeline Trends: Application volume and approval trends over time

🧪 Testing

Run the automated test suite:

python test_api.py

Manual testing examples:

# Health check
curl http://localhost:5003/

# Submit application
curl -X POST http://localhost:5003/loan-application/submit \
  -H "Content-Type: application/json" \
  -d '{"name":"Test User","email":"test@example.com","phone":"+1234567890","region":"AMERICAS","country":"United States","income":80000,"debt":20000,"credit_score":720,"loan_amount":200000,"loan_purpose":"Home Purchase"}'

# View dashboard
curl http://localhost:5003/dashboard/overview

📁 Project Structure

.
├── server.js                   # Express application entry point
├── db.js                       # PostgreSQL connection & schema bootstrap
├── loanService.js              # Loan persistence helpers
├── verificationService.js      # Verification workflow logic
├── seedData.js                 # Stock data seeder
├── seedLoanData.js             # Sample loan generator
├── start.sh                    # Helper script (seed + start server)
├── package.json                # Backend dependencies & scripts
├── docker-compose.yml          # Multi-container setup
├── Dockerfile                  # Backend container image
├── frontend/                   # React application
└── API_DOCUMENTATION.md        # Detailed API docs

⚙️ Configuration

Verification Rules (in verificationService.js):

  • MAX_DTI_RATIO = 0.4
  • MIN_CREDIT_SCORE = 650
  • INCOME_TO_LOAN_RATIO = 3
  • MAX_LOAN_AMOUNT = 1_000_000
  • MIN_INCOME = 30_000

Generate Sample Data:

npm run seed:stocks     # load stocks.csv
node seedLoanData.js 50 # create and process 50 apps

🔮 Future Enhancements

High Priority

  • Asynchronous processing with Kafka/Celery
  • Real email integration
  • Document upload and OCR
  • Real-time dashboard with WebSockets

Medium Priority

  • Admin panel for manual review
  • External credit bureau integration
  • Multi-factor authentication
  • Role-based access control

Nice to Have

  • Machine learning for fraud detection
  • Mobile app
  • GraphQL API
  • Blockchain audit trail

📝 Production Recommendations

  1. Database: Migrate to PostgreSQL
  2. Caching: Add Redis
  3. Queue: Use Kafka/RabbitMQ
  4. Monitoring: Implement APM
  5. Security: Add authentication, rate limiting
  6. Scalability: Deploy with Kubernetes

👥 Entities

  • Client: Applies for loan
  • Vendor: (Future) Views and processes applications
  • System: Automated verification engine

Built with ❤️ using Node.js, PostgreSQL, and Docker