I’ll give binomial distribution a shot
One type of operational risk is process risk. So let’s say we have a conveyor belt that puts coke caps on coke bottles. Let’s say it it does it 30 bottles per second.
Let’s say that on average, every 1000th bottle has an issue. It may be the 998th bottle, or the 1013th bottle, but it’s always around the 1000th bottle.
I would say that this follows a binomial distribution because the risk occurs not on every 1000th bottle on the dot, but AROUND the 1000th bottle (low variability).
Does this sounds reasonable?
I can’t really think of an example where there’s no frequency relative to the mean - If that’s the case wouldn’t we know exactly when the risk will occur (ex/ every 1000th bottle on the dot), meaning we can just exercise an action to stop the risk from occurring?