Assess whether a score that never fails is a control or theater (11f138)

Situation

A score that never sits with enterprise AI control-plane owner because a scorecard that rated 100% of outputs 'acceptable' hit a bank running three models on the same credit file. Evidence is vendor MSA clauses on training, indemnity, and subprocessors; write the AI Governance Layer Control Plane and Scoring option that extract can carry.

Decision

Enterprise AI control-plane owner in a bank running three models on the same credit file must choose A score that never fails is a control / Theater using vendor MSA clauses on training, indemnity, and subprocessors after a scorecard that rated 100% of outputs 'acceptable'.

Hypotheses to test

• A scorecard that rated 100% of outputs 'acceptable' is noise around an already-controlled Control Plane and Scoring process in a bank running three models on the same credit file, given vendor MSA clauses on training, indemnity, and subprocessors.
• A scorecard that rated 100% of outputs 'acceptable' is the event in vendor MSA clauses on training, indemnity, and subprocessors that forces A score that never fails is a control for enterprise AI control-plane owner under AI Governance Layer.
• Vendor MSA clauses on training, indemnity, and subprocessors shows a one-file miss after a scorecard that rated 100% of outputs 'acceptable', not a Control Plane and Scoring program failure.
• Vendor MSA clauses on training, indemnity, and subprocessors cannot decide a score that never yet after a scorecard that rated 100% of outputs 'acceptable'; hold is the only AI Governance Layer close a bank running three models on the same credit file can defend.

Analysis required

• Map the control-plane score in vendor MSA clauses on training, indemnity, and subprocessors to the policy gate enterprise AI control-plane owner can enforce.
• Name the override that would let a score that never proceed without a silent bypass.
• Test whether a scorecard that rated 100% of outputs 'acceptable' changed routing, logging, or human-in-the-loop on the live agent path.
• For this AI Governance Layer Control Plane and Scoring file, read vendor MSA clauses on training, indemnity, and subprocessors against a scorecard that rated 100% of outputs 'acceptable' and write the one fact that would move a score that never for enterprise AI control-plane owner.

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