there are a total of about 60 measures. Most measures are basic. There are some that are derived from other measures and also depend on dim attribute types. There are also 10 measure attributes that are more like buckets.
In financial services it's not unusual to have lots of measures. I would have expected buckets almost by definition to belong in a bucketing dimension (or dimensions) rather than a measure.
When you say some measures are derived from dimensions, that sounds very like you don't have a normalized data warehouse behind this. If you had a sufficiently normalized data warehouse (or even just an ODS) you could populate your derived measures from it without having to derive them from dimension data. For any complex data warehouse solution, don't try to populate a star schema direct from sources via ETL/staging. Keeping the storage (Data Warehouse) and presentation (Data Mart) layers separate will save you and your users lots of effort and frustration in the long run.