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AI Underwriting Assistant Implementation Plan

Overview

This document outlines the development plan for the AI Underwriting Assistant, a sophisticated system for automating commercial real estate document analysis and risk assessment.

Phase 1: Enhanced Document Processing (2 Days)

1. Document Extraction Service Improvements

  • Support multiple file formats:
    • PDF (with OCR)
    • Excel spreadsheets
    • Word documents
  • Intelligent layout detection
  • Specialized extractors for:
    • Rent rolls
      • Tenant names
      • Unit numbers
      • Square footage
      • Current rent
      • Lease start/end dates
      • Security deposits
      • Payment history
    • P&L statements
      • Revenue line items
      • Expense categories
      • NOI calculations
      • Historical comparisons
    • Operating statements
    • Lease documents

2. Data Normalization Engine

  • Standardize extracted data formats
  • Implement validation rules
  • Add confidence scoring for extracted fields
  • Create override/correction mechanisms
  • Data cleaning pipelines

Phase 2: Financial Analysis Engine (2 Days)

1. Core Financial Calculations

  • Comprehensive metrics implementation:
    • NOI analysis
    • Cap rate calculations
    • DSCR computations
    • Debt yield analysis
    • Operating expense ratios
    • Revenue/expense per square foot
  • Historical trend analysis
  • Variance detection

2. Market Analysis Integration

  • Market comparison capabilities
  • Trend analysis implementation
  • Historical data tracking
  • Forecasting capabilities
  • Market condition impact assessment

3. Risk Assessment System

  • Red flag detection:
    • Tenant concentration > 20%
    • Lease expiration risk
    • Below-market rents
    • Above-market expenses
    • Occupancy trends
    • Expense ratio anomalies
  • Risk scoring algorithm (0-100) based on:
    • Financial metrics
    • Market comparisons
    • Tenant quality
    • Property condition
    • Location factors
  • Market condition impact analysis

Phase 3: Frontend Development (2 Days)

1. React/TypeScript Setup

  • Initialize project with Vite
  • TypeScript configuration
  • Component architecture
  • State management (React Query)
  • API integration layer

2. Core Components

  • Document upload interface:
    • Drag-and-drop functionality
    • Progress tracking
    • File validation
    • Batch upload capability
  • Analysis dashboard:
    • Financial metrics display
    • Risk assessment visualization
    • Market comparison charts
    • Real-time processing status
  • Document management:
    • File browser
    • Status tracking
    • Batch operations
    • Search functionality

3. User Interface Features

  • Real-time processing status
  • Interactive data editing
  • Custom report generation
  • Export functionality
  • Error handling and user feedback
  • Responsive design

Phase 4: Integration & Testing (1 Day)

1. API Integration

  • Implement all endpoints:
    • POST /api/v1/documents/upload
    • POST /api/v1/analysis/financial
    • GET /api/v1/analysis/{analysis_id}
    • GET /api/v1/reports/{report_id}
    • PATCH /api/v1/analysis/{analysis_id}/override
  • Error handling
  • Rate limiting
  • Request validation

2. Testing Suite

  • Unit tests for all components
  • Integration tests
  • End-to-end testing
  • Performance testing
  • Security testing

3. Documentation

  • API documentation
  • User guides
  • Development setup instructions
  • Deployment guides
  • Architecture documentation

Phase 5: Deployment & Optimization (1 Day)

1. Infrastructure Setup

  • Docker containers
  • CI/CD pipeline
  • Monitoring setup
  • Logging implementation
  • Backup systems

2. Performance Optimization

  • Code optimization
  • Database query optimization
  • Caching implementation
  • Load testing
  • Performance monitoring

3. Security Implementation

  • Authentication system
  • Authorization rules
  • Audit logging
  • Data encryption
  • Backup systems

Success Metrics

  • Document processing accuracy > 90%
  • Processing time < 2 minutes per document
  • Financial spreading accuracy > 95%
  • Risk assessment correlation > 85%
  • System uptime > 99.9%

Technical Requirements

Development Requirements

  • TypeScript/React for frontend
  • Python 3.9+ for backend
  • PostgreSQL 13+
  • Docker for containerization
  • AWS for cloud infrastructure

Performance Requirements

  • API response time < 200ms
  • Document processing < 2 minutes
  • Concurrent user support: 100+
  • Storage capacity: Starting at 100GB

Security Requirements

  • SOC 2 compliance preparation
  • End-to-end encryption
  • Role-based access control
  • Audit logging
  • Data backup system