This is a question about insurance data. The response variable is whether or not a given claim will be >100k (i.e. large). The data is evaluated as of a certain date, and it includes claims that are only a few days old and some that are years old. Any of these claims that are not yet >100k could be if we evaluate them in a month or even in a year. The new claims (less than six months) are a lot less likely to be large, even if they will end up being that way - usually the amount that will be paid isn't known that early.
What I would like to know is if there is any value to a logistic model that predicts whether a claim will be large (given various characteristics) even though the data
