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Card #c13IR // #c13Synthesis

Prediction and agency should not be conflated. A credit model can estimate the probability that a borrower breaches a covenant. An agentic credit workflow must additionally determine which documents are authoritative, retrieve the relevant covenant language, reconcile contradictory data, simulate possible interventions, check approval limits, request human authorization when required, execute an admissible action, and preserve an audit trail. Increasing the parameter count of the predictor does not, by itself, supply persistent memory, permissions, transaction semantics, or institutional accountability.

— In our words · Source: Large Language Models in Finance (Miquel Noguer i Alonso)

[Use when]

Use when a team proposes a stronger model as the fix for an agent that lacks memory, permissioning, or an audit trail.

[Why it matters]

A bigger model buys none of the institutional machinery an agent needs — memory, permissions, transaction semantics, accountability. So 'we upgraded the model' is never an answer to 'who authorized this action,' and agents must be judged on the actions they induce, not the accuracy of their outputs.

Related principles

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