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Accounting › Spend & Risk

Finance Intelligence

Nothing here decides anything. Detectors produce scored observations with their evidence attached; a person opens the case and records what turned out to be true.

In Accounting → Spend & Risk · 10 screens

ScreenKindWhat it is ColumnsFieldsActions
Risk Queue Workspace What is open, what it is worth, and how quickly it is being worked — sorted by exposure rather than by score, because that sends people to the most expensive thing. 0 0 0
Risk Signals Read-only list A scored observation with its EVIDENCE attached. "Score 0.86" persuades nobody; the facts that produced it are what a person acts on. 15 0 2
Risk Cases List A person’s queue, with an outcome. The outcome is what closes the loop: confirmed fraud and dismissed noise are both training data, and a system that does not record which cannot improve. 15 15 1
Case Actions List What was done about it in the world, as opposed to in the case. 8 6 0
Risk Detectors List Each answers one question, is separately switchable and separately measured. A detector nobody can turn off is one that gets ignored wholesale the first time it is noisy. 15 16 2
Detector Performance Read-only list Precision — of the signals it raised, how many were real. The only number that decides whether a detector should keep running, and the reason outcomes are recorded at all. 14 0 0
Assistant Suggestions Read-only list Suggestion rather than detection, with the reasoning attached. "Because the last nine invoices from this supplier were coded 6410" is a reason a person can check; a confidence score is not. 10 0 1
Coding Patterns List A learned lookup rather than a model. For GL coding this beats a model on both accuracy and explicability, and a person can read it. 11 7 0
Narratives List The generated text and the edited one, both kept — the difference between them is the most useful feedback there is, and a narrative rewritten entirely was not worth generating. 9 7 0
Assistant Accuracy Read-only list Confidence is only useful if it is calibrated: a suggestion offered at 0.9 and accepted half the time is worse than one offered at 0.5 and accepted half the time, because the first one lies. 10 0 0

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