Backbone module · Wave 3 & annual run
The Baseline Standards are reported to require governance over AI and machine-learning models, with independent validation at least annually — covering accuracy, drift and bias. (Wording paraphrased from reporting on the circular — verify verbatim against the original CBN PDF.) Independent is the operative word: your detection vendor cannot mark its own homework. Ophir validates the model — we never build, sell or replace it.
Thresholds are the bank's model-risk appetite as approved by its model governance committee · illustrative figures.
Trailing 12 months · lower is more stable · sample data
The February event is the point of the annual run: drift was caught, the vendor retrained, and Ophir revalidated before the next cycle — all evidenced.
vs portfolio recall 91.3% · tolerance ± 2.0 pts · sample data
Region — North sits inside the ±2.0-pt tolerance band but within 0.6 pts of its edge, so it is held on quarterly monitoring rather than remediation. Independent judgement, documented — not a rubber stamp.
Sampling → back-testing → drift → bias → sign-off · ~2 seconds · sample data
The sealed, examiner-ready validation report appears here after the run.