Research & announcements

AI-drafted SAR narratives are proliferating, and most of them optimize for exactly the wrong thing: fluency. A defensible narrative is not well-written — it is well-grounded: every factual claim traceable to the case file, the suspicion articulated as reasoning, nothing material omitted. Examiners are starting to ask how the narrative was produced. Institutions need an answer.

Effective challenge is the load-bearing idea in model risk management, and it has always run on organizational willpower — which is exactly what erodes under deadline pressure and familiarity. Encoding challenge as an adversary node makes it structural: steelman the position first, then attack in both directions, at a rigor locked to the model's materiality.

Every AI system in a regulated workflow has two users: the operator who requests the output today, and the examiner who reviews it later — with subpoena-grade patience and no goodwill. Almost all AI product design serves the first user. The systems that reach core workflows will be the ones designed for the second.

The industry uses one word for two different things: the capability and the process. AI asks a model what it thinks; artificial reasoning defines how the system must think — as an explicit computation that records itself as it runs. Here is the distinction in full, what the term does not claim, and the falsifiable bet underneath it.

Every number an LLM produces is a prediction of what a number would look like. That's tolerable in a chatbot and disqualifying in a decision system. The engineering answer is deterministic tool-nodes — zero tokens, byte-reproducible — but the property that actually matters is authority: the model may cite the numbers, never recompute or override them.

Reg E’s error-resolution deadlines are absolute: 10 business days to investigate, 45 or 90 calendar days with provisional credit, no tolling for backlogs or turnover. Dispute volume has exploded with P2P fraud while investigation teams haven’t grown. The failure mode isn’t missing deadlines — it’s making them with investigations that can’t survive an exam.