In the context of operational risk management within a banking institution, estimating the loss severity distribution is crucial for assessing potential financial impacts due to operational risk events. However, operational risk analysts frequently encounter the challenge of limited historical loss data, which complicates accurate estimation. Given this scenario, what is the most effective methodology that an operational risk analyst can employ to estimate a bank's loss severity distribution despite the constraint of having insufficient historical operational risk loss data?