What makes your analysis better?
Our model is a very rigorous financial model incorporating thousands of stochastic simulations (layman’s term - “Monte Carlo Analysis”). We build this model acknowledging the reality that there is much we don’t know about the future. We don’t know what your revenue, expenses or investment returns will be next year. We don’t know whether you will get hit with a 1-in-100-year catastrophe expense next year, in 50 years, or some other time. As a result, what we do is build a model that randomly selects each unknown item for each year (i.e., revenue, expense and investment returns) based on the likelihood of it occurring (e.g., the equity market may have a return as high as +50% and it is possible that the model will select +50% for the equity returns in a given year, but the model will select a +7% return a lot more often). Then we use those numbers to determine the results at the end of the year. For a 100-yearmodel, 100 years of data are independently simulated. Our computer software reviews and logs the results. Then it starts the whole process over and creates a brand new 100-year model. For most of our projects, we create over 1,000 100-year models!
This large number of models allows us to understand what will happen to your perpetual care fund over a wide variation of future events. We then review the results of the models to determine probabilities of any particular event (such as the perpetual care fund balance moving to a specific target). These probabilities are reported to you in an easy-to-understand manner (e.g., “There is a 25% chance that the perpetual care fund will run out of money at some time within the next 100 years.”).