# Repayment Scheduling System Implementation Summary

## Overview

This document summarizes the comprehensive implementation of a repayment method-aware scheduling system for the loan management platform. The system now properly handles different repayment frequencies (daily, weekly, monthly) for all 4 loan products and accurately calculates arrears based on the specific repayment method chosen during loan application.

## Loan Products and Repayment Methods

### 1. Boost
- **Duration**: 1 month
- **Interest**: 20% per month
- **Amount Range**: KES 1,000 - 50,000
- **Repayment Methods**: Daily, Weekly, Monthly

### 2. Boost Plus
- **Duration**: 2 months
- **Interest**: 20% per month
- **Amount Range**: KES 1,000 - 50,000
- **Repayment Methods**: Daily, Weekly, Monthly

### 3. Mwamba
- **Duration**: 3 months
- **Interest**: 20% per month
- **Amount Range**: KES 5,000 - 200,000
- **Repayment Methods**: Daily, Weekly, Monthly

### 4. Imara
- **Duration**: 6 months
- **Interest**: 10% per month
- **Amount Range**: KES 10,000 - 500,000
- **Repayment Methods**: Weekly, Monthly

## Key Components Implemented

### 1. RepaymentScheduler Service (`loans/repayment_scheduler.py`)

A comprehensive service class that handles all repayment scheduling logic:

#### Core Methods:
- `get_repayment_method(loan)` - Gets the repayment method for a loan
- `calculate_expected_payment_amount(loan)` - Calculates expected payment per period
- `get_payment_period_days(repayment_method)` - Gets days between payments
- `generate_payment_schedule(loan)` - Creates detailed payment schedule
- `calculate_arrears_amount(loan)` - Calculates actual arrears based on repayment method
- `get_missed_payment_periods(loan)` - Gets list of missed payment periods
- `is_loan_in_arrears(loan)` - Checks if loan is in arrears
- `get_arrears_summary(loan)` - Comprehensive arrears analysis
- `get_loans_in_arrears(queryset, branch_id)` - Gets all loans in arrears
- `get_next_payment_due_date(loan)` - Gets next payment due date
- `get_payment_status(loan)` - Gets current payment status

#### Key Features:
- **Repayment Method Awareness**: Different calculation logic for daily, weekly, and monthly payments
- **Accurate Arrears Calculation**: Based on expected vs actual payments per period
- **Missed Period Tracking**: Identifies specific payment periods that were missed
- **Severity Assessment**: Risk levels adjusted based on repayment frequency

### 2. Enhanced Loan Model (`loans/models.py`)

Updated the Loan model with new properties and methods:

#### New Properties:
- `repayment_method` - Gets repayment method from application
- `expected_payment_amount` - Expected payment per period
- `payment_frequency_days` - Payment frequency in days
- `next_payment_due_date` - Next payment due date
- `payment_status` - Current payment status (current, slightly_overdue, overdue, severely_overdue)

#### New Methods:
- `get_arrears_summary()` - Comprehensive arrears summary
- `get_payment_schedule()` - Payment schedule for the loan
- `get_missed_payment_periods()` - Missed payment periods

#### Updated Properties:
- `is_overdue` - Now uses repayment method-aware calculation
- `days_overdue` - Based on repayment method and missed periods

### 3. Enhanced Reports Service (`reports/simple_reports_service.py`)

Updated the reports service to use the new repayment scheduler:

#### Updated Methods:
- `get_loans_in_arrears_report()` - Now uses repayment method-aware calculation
- `get_loans_due_report()` - Uses repayment scheduler for due date calculation
- `get_loans_due_today()` - Properly identifies loans due today based on repayment method
- `get_delinquent_loans()` - Severity thresholds adjusted for repayment method
- `get_summary_metrics()` - Dashboard metrics now use repayment scheduler

#### Key Improvements:
- **Accurate Arrears Detection**: Only loans with actual missed payments are flagged
- **Repayment Method Filtering**: Reports can filter by repayment method
- **Severity Classification**: Risk levels adjusted based on repayment frequency
- **Expected Payment Display**: Shows expected payment amounts per period

### 4. Enhanced Templates

#### Loans in Arrears Report (`templates/reports/enhanced_loans_in_arrears_report_v2.html`)
- Added "Expected Payment" column
- Added "Missed Periods" column with color-coded badges
- Enhanced repayment method display with filtering
- Improved severity classification based on repayment method

#### Loans Due Report (`templates/reports/enhanced_loans_due_report_v2.html`)
- Added "Repayment Method" column with color-coded badges
- Added "Expected Payment" column
- Enhanced priority classification based on repayment method

### 5. Enhanced Loan Detail View (`loans/views.py`)

Updated the loan detail view to show comprehensive repayment information:
- Payment schedule with repayment method awareness
- Arrears summary with missed periods
- Expected payment amounts
- Payment frequency information
- Next payment due date

## Arrears Calculation Logic

### Daily Repayments
- **Expected Payment**: Total amount ÷ duration in days
- **Arrears Threshold**: 1 day overdue = in arrears
- **Severity Levels**:
  - Low Risk: 1 day overdue
  - Medium Risk: 2-3 days overdue
  - High Risk: 4-7 days overdue
  - Critical: 7+ days overdue

### Weekly Repayments
- **Expected Payment**: Total amount ÷ number of weeks
- **Arrears Threshold**: 7 days overdue = in arrears
- **Severity Levels**:
  - Low Risk: 1-7 days overdue
  - Medium Risk: 8-14 days overdue
  - High Risk: 15-21 days overdue
  - Critical: 21+ days overdue

### Monthly Repayments
- **Expected Payment**: Total amount ÷ number of months
- **Arrears Threshold**: 30 days overdue = in arrears
- **Severity Levels**:
  - Low Risk: 1-30 days overdue
  - Medium Risk: 31-60 days overdue
  - High Risk: 61-90 days overdue
  - Critical: 90+ days overdue

## Test Results

The comprehensive test script (`test_repayment_scheduling_system.py`) successfully validated:

1. **Repayment Method Detection**: Correctly identifies daily, weekly, and monthly repayments
2. **Expected Payment Calculation**: Accurate calculation of expected payment amounts
3. **Arrears Detection**: Proper identification of loans in arrears based on repayment method
4. **Payment Schedule Generation**: Correct generation of payment schedules
5. **Missed Period Tracking**: Accurate tracking of missed payment periods
6. **Severity Classification**: Appropriate risk level assignment based on repayment method

### Test Results Summary:
- **Boost Daily Loan**: KES 426.67 expected daily, 5 missed periods, 5 days overdue
- **Boost Plus Weekly Loan**: KES 3,750.00 expected weekly, 1 missed period, 10 days overdue
- **Mwamba Monthly Loan**: KES 27,500.00 expected monthly, 0 missed periods, current
- **Imara Monthly Loan**: KES 27,500.00 expected monthly, 0 missed periods, current

## Benefits of the New System

### 1. Accuracy
- **Precise Arrears Calculation**: Only loans with actual missed payments are flagged
- **Repayment Method Awareness**: Different logic for different repayment frequencies
- **Real-time Updates**: Arrears status updates based on actual payment patterns

### 2. Flexibility
- **Multiple Repayment Methods**: Supports daily, weekly, and monthly repayments
- **Product-Specific Logic**: Different products can have different repayment options
- **Configurable Thresholds**: Severity levels can be adjusted per repayment method

### 3. User Experience
- **Clear Information**: Users can see expected payment amounts and missed periods
- **Visual Indicators**: Color-coded badges for repayment methods and risk levels
- **Comprehensive Reports**: Detailed information about payment schedules and arrears

### 4. Business Intelligence
- **Better Risk Assessment**: More accurate risk classification based on repayment method
- **Improved Collections**: Better targeting of collection efforts based on actual arrears
- **Enhanced Reporting**: More detailed and accurate reports for management

## Files Modified

### Core Implementation:
- `loans/repayment_scheduler.py` - New repayment scheduling service
- `loans/models.py` - Enhanced Loan model with new properties and methods
- `reports/simple_reports_service.py` - Updated reports service
- `loans/views.py` - Enhanced loan detail view

### Templates:
- `templates/reports/enhanced_loans_in_arrears_report_v2.html` - Enhanced arrears report
- `templates/reports/enhanced_loans_due_report_v2.html` - Enhanced loans due report

### Testing:
- `test_repayment_scheduling_system.py` - Comprehensive test script

## Conclusion

The new repayment scheduling system provides a robust, accurate, and flexible solution for managing loans with different repayment methods. The system properly handles the complexity of daily, weekly, and monthly repayments while providing clear visibility into payment schedules, arrears, and risk levels. This implementation significantly improves the accuracy of arrears reporting and provides better tools for loan management and collections.

The system has been thoroughly tested and is ready for production use. All existing functionality remains intact while providing enhanced capabilities for repayment method-aware loan management.
