- Enter an annual probability. Use the annual loss probability you want to examine. It is an assumption, not a personalized forecast.
- Choose the time horizon. Enter the number of years over which you want to estimate the chance of at least one event.
- Read the cumulative probability. The main result converts the annual assumption into the probability of one or more modeled events.
- Compare the no-loss probability. The complementary result shows the chance that none of the modeled events occur during the same horizon.
- Use expected count carefully. The expected event count is annual probability multiplied by years; it is an average, not a prediction of a whole number of events.
Long Term Care Insurance Loss Probability Calculator
Estimate the probability of experiencing at least one long-term care loss event over a selected number of years from an assumed annual probability. The calculator also shows the complementary probability of no modeled loss during the period and the simple expected number of events, which can help frame long-horizon risk scenarios. This is most useful when you want to translate an annual assumption into a multi-year perspective. A seemingly modest yearly probability can accumulate over a longer horizon, but the result depends completely on the entered rate and the simplifying assumption that each year has the same independent probability.
Enter your assumptions
%
years
Result
—
Probability of at least one modeled loss
Probability of no modeled loss—
Simple expected event count—
Annual probability used—
Time horizon—
Probability of no loss = (1 − p)^nProbability of at least one loss = 1 − (1 − p)^nExpected event count = p × n
Where:
- p = assumed annual loss probability as a decimal
- n = number of years in the time horizon
Assumptions: The annual probability is held constant and yearly events are treated as independent. Real long-term care risk can vary substantially with age, health, policy definitions, and other factors, so this is a mathematical scenario model rather than an actuarial estimate.
What the result means
The cumulative percentage represents the chance of at least one modeled loss over the selected horizon under the constant, independent annual-probability assumption.
Do not interpret the result as a personalized probability of needing long-term care unless the annual input itself comes from an appropriate individualized or actuarial source.
Given: Assume an 8% annual loss probability for a 20-year horizon.
Calculation: Probability of no loss = (1 − 0.08)^20 = 0.92^20 ≈ 0.1887, or 18.87%. Probability of at least one loss = 1 − 0.1887 = 0.8113, or 81.13%. Expected event count = 0.08 × 20 = 1.60.
Result: The modeled probability of at least one loss over 20 years is about 81.1%.
Interpretation: The cumulative probability is much higher than the 8% one-year rate because the scenario spans many years. The 1.60 expected count is an average across repeated hypothetical scenarios, not a claim that exactly 1.6 events will occur.
Why not multiply the annual probability by the number of years for the main result?
Simple multiplication can exceed 100% and does not calculate the probability of at least one event. The complement formula accounts for repeated opportunities for an event to occur.
What does independence between years mean?
It means the model treats whether a loss occurs in one year as not changing the probability in another year. That is a mathematical simplification.
Can the annual probability change with age?
In reality it may. This calculator holds one rate constant, so you can test different periods separately if you want to examine changing assumptions.
What does an expected event count below 1 mean?
It is an average over many hypothetical repetitions, not a minimum or maximum. An individual path can still have zero, one, or multiple events.
How is this different from the expected claim calculator?
This tool focuses on the probability of one or more events over time. The expected claim calculator combines a probability with a modeled dollar payout.