You can use regression splines or lowess to locally weight the areas with low data based on what you do know, it keeps your parameter count down but still performs well even at the tails.
So I’m not against using age, but binning it coarsely is the issue when it can be handled much more granularly.
64-65 is probably a negligible amount of risk increase, but 64-69 is going to be much bigger. Looking at younger ages the effect is more extreme where they’re probably charging late 20’s drivers more because they’re pooled with low 20’s.
Anyway, on average it probably works out the same, but in practice I never bin data where I can avoid it, since you get better information looking at it as a continuous range.
I don’t think you need to post your address like the old days, I would never notice nor care about such an omission.
I do always look at job history, and I don’t out a lot of stock in the skills section because most of the time people lie or exaggerate there.