Not every risk can be treated as a statistical bet. A small class of outcomes, seizure, debanking, lost custody, a rail turning off, live in a category where a single bad realisation ends the ability to play the game again. Those get separate rules, chosen calmly, ahead of time. The mistake is to treat them as high-probability findings among a portfolio of others, because the arithmetic that works for the portfolio does not work for the class.
We score both; every signal carries a probability estimate and a consequence class. The action band is derived from both. A modest-probability signal on a ruin-class risk lands at a higher band than a high-probability signal on a paperwork risk.
The framing changes conversations with clients. It stops being "how sure are you" and starts being "what does acting on this cost, and what does not acting on it cost." Those two numbers do most of the deciding on their own.
The consequence classes are short and stable. We do not add a new class because a particular case would benefit from one. We fit the case into the existing classes and revisit the taxonomy only when the same misfit keeps appearing across quarters.
Most decision systems, private and institutional, treat every finding as if its cost were the same. It never is. Some errors are absorbed by a phone call and a re-review; others end a relationship, a mandate, or a residency plan that took two years to build. The weight is the part the model has to carry, not the analyst on the day.
The reason to build this in early is that under time pressure people default to whichever risk is easiest to describe. Weighting by consequence forces the harder conversation about what a wrong answer actually costs, before there is a wrong answer to defend.