Abstract
An insurance fraud detector allocates investigative attention before it establishes that misconduct occurred. This conceptual analysis examines the graph, temporal, and multi-agent research problem identified by CHIMERA through that operational distinction. It proposes an evaluation in which the claim episode, information available at the decision time, investigator workload, and independently adjudicated outcome remain connected. The argument separates relational suspicion from proof, predictive attribution from an explanation of wrongdoing, and a high model score from a defensible intervention. Calibration, selective review, and parameter-efficient adaptation enter as supporting components whose costs and failure modes must be measured. No claims database was analyzed and no CHIMERA implementation was trained or reproduced. The result is a prospective design for assessing a fraud-screening system at the point where a statistical flag becomes an investigation decision.
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Copyright (c) 2026 Ethan Parker, Liam Carter, Noah Bennett (Author)