Endorsements - Workmen Compensation (WC)¶

Overview¶

Based on 2,555 policies from Premia UAT database.

Common Endorsement Types in UAE¶

Based on UAE insurance market practices for Workmen Compensation policies, the most common mid-term changes include:

1. Wage Roll Adjustments¶

Most common endorsement for WC policies: - Increase in annual wage roll (business expansion) - Decrease in annual wage roll (workforce reduction) - Additional employees hired mid-term - Employees terminated or transferred

Premium Impact: Pro-rata adjustment for remaining period

2. Industry Classification Change¶

When business activity changes: - Change in occupational risk category - Addition of new business activities - Change from low-risk to higher-risk operations

Premium Impact: Rate re-classification and premium recalculation

3. Add Employer's Liability Extension¶

Extending coverage beyond statutory WC: - Add Common Law liability coverage - Add Sharia Law liability coverage - Increase coverage limits

Premium Impact: Additional premium for extended coverage

4. Policy Period Extension¶

Short-term continuation of coverage: - Extend beyond expiry date - Bridge coverage until renewal - Temporary extension (typically 1-3 months)

Premium Impact: Short-rate calculation for extension period

5. Change in Policy Details¶

Administrative changes: - Company name change (due to restructuring) - Business address relocation - Contact details update

Premium Impact: Usually no premium impact

Cancellation Rules¶

For Workmen Compensation policies:

Full Cancellation¶

Allowed when: - Business permanently closed - All employees terminated - Coverage transferred to another insurer

Refund Calculation: - Short period rates typically apply - OR pro-rata if configured - Minimum earned premium may apply

Partial Cancellation¶

Allowed when: - Specific employee categories removed - Certain business units excluded - Wage roll significantly reduced

Refund Calculation: - Pro-rata for remaining period - Based on reduced wage roll

Database Structure¶

Endorsement Tables¶

PGIT_ENDT_REASON - Endorsement master
PGIT_POL_ENDORSEMENT - Endorsement details
PGIT_POL_RISK_ADDL_INFO - Updated risk data

Common Endorsement Fields¶

ER_TYPE - Endorsement type code
ER_REASON - Reason for endorsement
ER_FM_DT - Effective date
ER_PREM_ADJ - Premium adjustment
ER_SI_ADJ - Sum insured adjustment

Premium Adjustment Logic¶

Increase in Wage Roll¶

Additional Premium = (New Wages - Old Wages) × Rate × (Days Remaining / 365)

Decrease in Wage Roll¶

Refund Premium = (Old Wages - New Wages) × Rate × (Days Remaining / 365)

Coverage Addition¶

Additional Premium = Coverage Premium × (Days Remaining / 365)

Validation Rules¶

When processing WC endorsements:

Wage Roll Updates
Verify new wage declaration
Confirm employee count
Validate against trade license
Rate Changes
Check if industry classification changed
Recalculate if risk profile altered
Apply new rates prospectively
Coverage Changes
Ensure mandatory coverage maintained
Validate coverage combinations
Check regulatory compliance

PL/SQL Packages¶

Endorsement processing typically uses: - PGIPK_ENDORSEMENT - Main endorsement package - PGIPK_ENDT_CANCEL - Cancellation logic - PGIPK_CALC_PREMIUM_* - Premium recalculation

Integration Considerations¶

When implementing WC endorsements:

Wage Roll Declaration
Annual wage audits
Mid-term adjustments
Final audit at expiry
Premium Adjustments
Calculate pro-rata amounts
Handle additional premium collection
Process refunds if applicable
Documentation
Generate endorsement certificate
Update policy schedule
Notify all parties

Data Limitations¶

Note: The current dataset shows 0 endorsements for WC product 5030. This analysis is based on: - Standard insurance practices - Premia system structure - Comparable product patterns - Database schema analysis

For actual endorsement frequencies and types, additional data extraction from PGIT_ENDT_REASON and related tables would be needed.

Data Source: Analysis of 2,555 WC policies from Premia UAT. Endorsement section based on system structure and standard practices due to lack of endorsement records in current dataset.