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Notes

From the work, and from commerce. Published on Substack, copied here as written.

Pending Outlines

Outlines for pieces that have to come from the work, not generated. High level ideas, not yet ready.

  1. Who pays for fraud

    From the work: allocation, total cost of fraud, and what charging a P&L actually rewards. Write from rooms and numbers, not the general case.

    • Every fraud loss is paid by someone. The live question is which P&L is made to look responsible.
    • Loss is only the visible part of the bill: operating expense, false positives, late write-offs, disputes, brand.
    • An allocation model is an incentive machine. Who is overcharged starts caring about prevention; who is undercharged starts caring about customer experience.
    • ROI in fraud is a story with assumptions. A handsome ROI with miserable customer impact is a transfer, not a success.
    • If you cannot say, in language a product owner will accept, why their customers are in the queue, you have a dashboard rather than a strategy.
  2. The control that performs

    The difference between a control that changes what someone may do, and the artefacts that prove such a control exists.

    • Two systems: the one that changes behaviour, and the one that produces evidence. Careers are often made in the second.
    • Test: if this control disappeared on Monday, what would break on Tuesday? If the answer is a missing slide, it is a ritual.
    • A real control has a cost someone does not want to pay. A long inventory that makes nobody angry is a warning.
    • Governance, used precisely, is plumbing: who may do what, how we know, what happens when they did not.
    • Generative models make the artefacts cheaper. They do not watch a queue or own a miss.
    • Prefer a smaller inventory: named owners, a failure mode in a sentence, a metric that would move if the control stopped working.
  3. What a model does not know

    Where models help in this work, and where they cannot replace the person whose name is on the exception.

    • Banks do not lack text. They lack people who are still in the room when the text is wrong.
    • Fluency in the house dialect is not knowledge. Tired people waving through a pack that sounds right are the actual control environment.
    • What the model does not know is local: residuals in the loss line, vendor feeds patched with a default, the report a senior person last trusted in 2019.
    • Use: draft, summarise, point at fields. Do not use as system of record, policy, or attestation.
    • A number without a lineage a sceptical person can walk is a paragraph, not analysis.
    • Stay exception-native. Who owns the miss?