# Description
Creates 2 new models in the scope of flagging: how good are we at identifying "at risk" bookings vs. 1) the number of claims generated and 2) the number of submitted payouts?
This only applies for Protected Bookings in New Dash that have been completed (14 days after the check-out) with potential resolutions appearing in Resolutions Center.
The first table `int_flagging_booking_categorisation` contains all the heavy logic to categorise the bookings.
The second view `int_flagging_performance_analysis` computes standard binary classification scores, for the 2 possible ways of tracking.
Tables are already in prod to help you understand while reviewing. You'll see that the figures are still quite low, specially due to small amount of claims/submitted payouts. This makes the true positives being just... 1.
There's heavy test and documentation coverage to ensure there's no mistakes on the computation.
# Checklist
- [X] The edited models and dependants run properly with production data.
- [X] The edited models are sufficiently documented.
- [X] The edited models contain PK tests, and I've ran and passed them.
- [X] I have checked for DRY opportunities with other models and docs.
- [X] I've picked the right materialization for the affected models. **Materialising as table the first model despite being just 1 record since otherwise tests takes ages**
# Other
- [ ] Check if a full-refresh is required after this PR is merged.
Related work items: #29284
a2cad661dd