Hey there!
So I’m spending this last week, scratching my head on how much profit loading to select.
You probably are in the same situation…
Personally, I’m juggling between:
 Simple way of loading expected claims by a fixed factor.
(additive and or multiplicative)  Be fancy and apply loading factors using specific rules.
That’s when I thought about reusing my market simulation, discussed here and here.
Let’s use my top 10 models, which are all different algorithms.
It would be a proxy for the leaderboard top 10 insurers market.
Then, because the top 10 leaderboard all show profitability, it naturally leads to this optimization question…
Question
What’s the minimal loading required so that all 10 insurers are profitable?
And for simplicity, let’s use a simple multiplicative approach.
Response
A lot. …
But before spoiling you…
Comprehension of the leaderboard.
Perhaps I’m oversimplifying, but is it reasonable to think of the top 10 insurers as a “final market”?
So that their respective profit and market share would be the results of those unique top 10 insurers going against each other? (no other insurers involved)
If so…

How do I reconcile the fact that the sum of the top 10 insurers, on week 10, have a combined market share of 65.4%, which is far from 100%?
Should it be ideally closer to 100% ? 
Should I expect the top 10 insurers to all be profitable when going against each other?
^^ I understand that there are averages along the way, but if the staff can chime in on that, it would be great!
By now, perhaps you see how those questions are crucial assumptions in the simulation analysis.
Response
Note that the minimal loading required is highly sensitive to the actual losses occurring in the test set.
Ran the simulation on first 4 seeds, which represents 4 different holdouts.
… … … … Minimal Loading%
Seed 17 … . .32%
Seed 42 … …36.5%
Seed 666 … . 41%
Seed 1313 … 31.7%
Results indicate that a loading between ~30% and ~40% is required, so that all insurers are profitable.
It seems high to me, what do you think?
Is it high because of how the problem is framed… that all 10 insurers must be profitable? Which leads me back to my two comprehension questions…
EDIT:
Ran the next seed and loading required dropped to 25%.
It becomes clear that the actual losses randomness is important.
Either
 to prepare for more losses , you shoot for a hefty loading,
 you gamble that year 5 will have smaller losses and apply smaller loading.