The beta distribution is defined by two parameters ($\alpha$ and $\beta$), which can be determined completely if the mean (Expected Loss) and variance (Unexpected Loss squared) are known. Because it is totally characterized by EL and UL, there are no additional parameters left to calibrate the tail shape independently. Therefore, the tail behavior of the beta distribution depends entirely on the ratio of EL to UL, which can be a significant drawback when fitting the heavy right tails typically observed in credit loss distributions. Option A is incorrect because the beta distribution only has two parameters. Option B is incorrect because setting $\alpha = \beta$ makes the distribution symmetric, whereas credit losses are highly skewed. Option D is incorrect because once a distribution is fitted, the capital multiplier can be determined from its percentiles.