Gratuity Report Software: How it works?

Simplified UI + Latest Tech = Satisfying UX


Gratuity report: An AI-based innovative approach

We have developed a cloud-based software that performs all the required Gratuity Report calculations in les than 2 minutes. This allows the user to generate a 25+ pages Gratuity and/or Leave Encashment Reports instantly. Both, Gratuity Report and Leave Encashment Report are fully compliant with AS15 and IndAs19 accounting standards.

Ours is, perhaps, the first-of-its-kind actuarial software in the world. All you need to do is input the data and the report gets generated instantly.
We use AI algorithms extensively to achieve accurate results in an efficient manner.

We have automated all the calculations, thus leaving no scope for human error.

Did you know?
Government of India identified our Gratuity Report software as one of the top innovative products in the first ever #StartupIndia Innovation Week Challenge held in January 2022.

Inputs: Simple UI

We have simplified the entire journey for the users seeking gratuity reports for the first time by dividing inputs into 2 minimalist sections: Assumptions and Employee details.

Assumptions are editable cell inputs for:

  • Salary escalation rate  <– click on the link for more info
  • Attrition rate <– click on the link for more info
  • Salary increment month
  • Retirement age
  • Vesting period <– minimum number of years in service for the employee to be eligible for gratuity payout

Employee details can be copy pasted from Excel as a single table and include:

  • Employee name and ID
  • Date of birth
  • Date of joining
  • Monthly salary (Basic + DA) at beginning and end of the valuation period in respective columns

Fully Compliant: Methodology & Processes

Actuarial valuation of gratuity liability involves:
  • Calculation of net defined benefit obligation (or DBO) liability using the PUC (Projected Unit Credit) method. This is as prescribed by both IndAS19 and AS15 accounting standards. 
  • Projection of future expected gratuity payout cashflow and its estimate from the date of valuation to the date of death / retirement for every individual employee.
  • While the market practice may involve estimating the above cashflows on annual basis, for a greater accuracy we project cashflows on monthly basis.
  • Further sensitivity analysis of the actuarial calculations based on various iterations of discount rate, salary escalation rate, attrition rate and other assumptions as required.

Latest Tech: 1crore+ cells calculated every minute

Actuarial valuation of gratuity liability entails complex calculations. Several lakhs of cells are calculated to estimate gratuity liability for each employee. A small snippet of these calculations is mentioned below:
  • Projection of monthly cashflows for each individual employee for up to 65 years in future. Starting with: 65 years x 12 months = 780 cells
  • Calculation of various probabilities (at least 4 different types) used to project discounted cashflows for each type of exit respectively. These involve at least 30 calculations for each month of projection. Thus taking total calculations to more than 20,000 cells per employee (conservative estimate).
  • Then, we repeat the calculations for each employee several times (at least 10, often more) to meet reporting requirements of the accounting standards. Thus, on a conservative basis, for each employee, there are more than at least 2 lakh cells worth of calculations.
  • As such, for a small company with 100 employees, there are more than 2 crore cells calculated (on a conservative basis).

All these calculations are then presented to the user in a nice and concise pdf-format gratuity report, fully compliant with the respective accounting standards, AS15 or IndAS19.

The entire process mentioned in this section takes 2 minutes (or lesser). We achieved this feat by using advanced cloud- computing technology, without compromising on the accuracy of the gratuity report in any way. If anything, the accuracy has instead been enhanced due to elimination of human errors risk.

Know more

We recommend reading the following articles for further information:

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