The analysis of extreme events is challenging, but important, as occurrence of an extreme is usually associated with high damage. In general, frequency of extremes are modelled using Poisson distributions while damage is modelled using heavy-tailed distributions or distributions that allow for extreme outcomes such as e.g. the Lognormal, Weibull or Burr distribution. These distributions are widely used to fit damage data and help to better represent the tails of the distribution. There are certain specific contexts (e.g. local studies, extremely rare events) where data available may not be sufficient to fit a distribution or derive parameter values for the frequency and damage distributions. This paper discusses such circumstances and examines the potentials of using expert opinions in order to obtain values of the distribution parameters. In particular we illustrate how to solve for parameters so that common distributions satisfy two quantile conditions. An illustration of the method is provided for the application of quantifying the risk of bushfires in a local area in Northern Sydney.