How to Prepare Clean Employee Data for Your Consulting Actuary

The single most common cause of delayed IAS 19 valuation reports and blown audit deadlines is the transmission of corrupted, incomplete, or illogical HR census data. An actuarial model is computationally rigorous; if the foundational data is flawed, the resulting liability outputs will be indefensible.

Here is how HR and Finance teams can perfectly structure their data handoff.

1. The Holy Trinity of Dates

Every employee row in your spreadsheet must contain three pristine, mathematically logical dates:

• Date of Birth: Critical for calculating mortality and retirement decrements.
• Date of Joining: The absolute starting point for calculating accrued years of service.
• Valuation Date: The exact cut-off date for the financial reporting period (typically December 31st).

Data Scrubbing Tip: Ensure that the Date of Joining is strictly greater than the Date of Birth by a reasonable working age threshold (e.g., 18 years). Accidental inversions in Excel formats (MM/DD/YYYY vs DD/MM/YYYY) are a notorious source of fatal model errors.

2. Salary Integrity

The "Current Salary" field must exactly match the definition of the salary used for terminal benefit calculations in your local jurisdiction.
For example, in the UAE, End-of-Service Gratuity is typically driven by the Basic Salary. If your extraction software inadvertently dumps the Gross Salary (including housing and transport allowances) into the actuarial data template, the actuary will calculate a liability that is massively—and incorrectly—inflated.

3. Structural Flags

Include binary flags for critical employment states. Is the employee on an active contract, or are they currently serving their notice period? Have they already resigned? Employees who have formally resigned prior to the valuation date but have not yet been paid out are generally reclassified as short-term payables rather than long-term actuarial obligations.

By proactively scrubbing this data before sending it to your actuarial consultants, you enable them to immediately begin constructing the liability curve, rather than spending weeks engaged in frustrating email queries.