Think about it like this. Mostly in finance we assume that we have the equivalent of a standard dice. That is, while we assume we don't know what number will come up next, we think that we know the distribution of numbers perfectly. In fact the real situation is much more akin to throwing a dice where we have imperfect knowledge of what numbers are on the faces. They might be 1 to 6; but they also might be 1 to 5 with the 1 repeated; or 2 to 7; or something else entirely. Worse, the numbers are changed by the malevolent hand of chance on a regular basis. Not so often that we know nothing about the distribution, but often enough that we cannot be sure that the current market will be like the past.
Thus our risk estimates are potentially wrong for at least two reasons. We might have been wrong about the past distribution. And even if we got that right, it might be different in the future. In other words, you can't manage risk effectively by assuming you know the distribution - to be effective, you really must assume that you don't. Thus you don't just want your risk to be low enough based on one model: you want it to be low enough based on all (or at least all likely) models.