I am genuinely interested in understanding a little more about the risk aggregation approaches that are out there. I have been recently working on building an operational risk model under Basel 3.1, where the following approach applies. Risks are being modelled via LogN distributions (with the option to use Weibull or Pareto). Given there is no data history, an optimistic and a pessimistic loss is being used (e.g. the 50th and the 90th percentile of the distribution) in order to back solve for t