Model benefits, premiums, mortality, and reserves accurately. Compare payment patterns, lifetime values, and reserve changes. Understand long-term protection costs using simple assumptions and outputs.
| Input | Example Value |
|---|---|
| Current Age | 35 |
| Maximum Age | 100 |
| Sum Assured | 250000 |
| Premium per Payment | 180 |
| Payment Frequency | Monthly |
| Premium Paying Years | 30 |
| Annual Interest Rate | 4.50% |
| Annual Mortality Rate | 0.35% |
| Mortality Improvement | 0.00% |
| Annual Benefit Growth | 0.00% |
| Expense Loading | 8.00% |
This model uses a simplified actuarial present value method.
A whole of life policy calculator estimates the long-run cost and value of permanent life cover. It combines mortality, discounting, premium timing, and benefit growth. This gives a structured view of policy economics. It also helps you test how small assumption changes affect a lifelong contract.
Whole life insurance can remain active for decades. That makes early pricing assumptions very important. A slightly lower interest rate can raise present value costs. A higher mortality rate can lift expected claims. Longer premium periods can improve funding strength. Scenario testing is therefore useful before comparing plans.
This calculator uses current age, terminal age, sum assured, periodic premium, and payment frequency. It also uses annual interest, annual mortality, mortality improvement, benefit growth, expense loading, and premium paying years. Together, these inputs create a practical approximation for actuarial review, budgeting, and long-term protection planning.
Each future year has a survival probability and a death probability. The projected benefit is multiplied by the chance of death in that year. That creates an expected claim value. The discount factor then converts that future expected claim into present value. Premium value is built from premiums paid while the insured is alive at the start of each year.
The output reports actuarial present value of death benefits, present value of net premiums, reserve surplus or shortfall, adequacy ratio, and an estimated fair annual premium. It also estimates the probability of death before the selected terminal age. These measures help reveal whether the current premium pattern appears strong, weak, or roughly balanced.
Try changing benefit growth when inflation protection matters. Adjust mortality improvement to test healthier future expectations. Shorten or lengthen premium years to examine affordability. Compare monthly and annual patterns by changing payment inputs. These scenario checks help users see how funding design alters long-term whole of life policy balance.
This calculator is best for education, sensitivity testing, and first-pass review. It does not replace an insurer illustration, underwriting result, or licensed advice. Real pricing may use detailed mortality tables, lapses, policy fees, bonuses, taxes, and product-specific rules. Still, the model gives a fast way to understand whole of life policy value with clear mathematical logic.
A whole of life policy is permanent life cover. It is designed to stay active for the insured lifetime, provided policy conditions are met. It usually pays a death benefit whenever death occurs, not only during a fixed term.
No. This tool provides a simplified mathematical estimate. It helps with planning and comparison. Actual insurer pricing can include underwriting, detailed mortality tables, fees, policy bonuses, taxes, and product-specific features that this model does not fully capture.
The interest rate controls discounting. Lower rates make future claims more expensive in present value terms. Higher rates reduce present value. Because whole life coverage can last many decades, small interest changes can move the result meaningfully.
Mortality improvement reduces the future mortality assumption over time. It reflects a scenario where survival improves in later years. Using it can lower projected claim probability in each future year and slightly change policy value.
Actuarial present value is the current value of expected future cash flows after weighting them by probability and discounting them to today. For this policy, it measures the value of expected death benefits and expected premiums.
That usually means the entered premium pattern may be too weak for the selected assumptions. A low premium, short payment period, low interest rate, or high mortality assumption can make expected benefits exceed the present value of premiums.
Setting premium paying years to 0 tells the model to continue premiums for life, up to the chosen terminal age. This can materially increase the present value of premiums and improve the policy funding position.
Yes. Benefit growth is useful for testing rising coverage levels. It can approximate inflation-linked protection scenarios. However, it remains a simplified assumption, so real products with bonuses or indexation rules may behave differently.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.