Cheap Checks, Costly Decisions: What AI Really Costs in Anti-Money-Laundering Reviews
Year: 2026
Type: preprint
Abstract: Banks use AI to prepare anti-money-laundering reviews of their customers. Even when the automated check becomes cheaper, analysts may have to spend more time verifying the evidence and recording who was authorised to take the decision. This article proposes a comparison protocol. It prices the full review episode, with labour in three layers: preparation, verification, and decision-and-record. Workflows are compared only when they meet the required decision quality and can be reconstructed. Vendor surveys indicate substantial expenditure, and research from other domains suggests that verifying automated output takes effort, but neither establishes a net cost increase in customer reviews. A single ledger observation from DDYs Global, which the author co-founded, illustrates how costs can be recorded. The central hypothesis is that AI assistance can move enough work into verification and recording to reverse the ranking that the cost per check suggests. A proposed pilot makes it testable.
Author: Neuhaus, Daniel
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7221523243
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