A Model That Looks Good Until the State Changes

A decision model performs well on its validation dataset: accuracy is acceptable, calibration looks reasonable, standard test cases pass. The model appears ready.

AnantVerify tests the model under controlled state transformations. Most individual transformations pass. Then two otherwise acceptable changes are combined — and the decision fails. Neither conventional test exposed the interaction, because neither condition was problematic on its own.

The question changes from “did the model pass validation?” to “under what decision conditions has the model actually been assured?” The model-risk team can see the failed interaction, the affected decision region, the coverage gap and the evidence behind the required behavior.