AI as an Attributable Representation Channel: When AI-Mediated Suitability Claims Become a Governance Failure

Public-facing AI assistants increasingly provide guidance to consumers on financial products, risks, suitability, and comparative options, often in high-intent decision contexts. While firms typically do not author or control these systems, representations relating to suitability and risk may nonetheless create attribution or accountability exposure under existing conduct and consumer-protection regimes. This paper examines a governance gap emerging in financial services: supervisors and internal audit functions increasingly expect firms to evidence oversight of AI-mediated representations, yet most institutions lack audit-grade artifacts demonstrating such monitoring. Using an illustrative scenario, the paper shows how Reasoning Claim Tokens (RCTs) can function as evidentiary control objects that document repeatable omission of suitability constraints without requiring access to AI model internals or operational control over third-party systems. The analysis situates AI-mediated omission risk within established conduct-risk and suitability doctrines and clarifies the governance implications of detectability, repeatability, and foreseeability.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-31
DOI
https://doi.org/10.5281/zenodo.18105273
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

AI as an Attributable Representation Channel: When AI-Mediated Suitability Claims Become a Governance Failure

Tim de Rosen
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

AI as an Attributable Representation Channel: When AI-Mediated Suitability Claims Become a Governance Failure

Tim de Rosen
article en

Abstract

Public-facing AI assistants increasingly provide guidance to consumers on financial products, risks, suitability, and comparative options, often in high-intent decision contexts. While firms typically do not author or control these systems, representations relating to suitability and risk may nonetheless create attribution or accountability exposure under existing conduct and consumer-protection regimes. This paper examines a governance gap emerging in financial services: supervisors and internal audit functions increasingly expect firms to evidence oversight of AI-mediated representations, yet most institutions lack audit-grade artifacts demonstrating such monitoring. Using an illustrative scenario, the paper shows how Reasoning Claim Tokens (RCTs) can function as evidentiary control objects that document repeatable omission of suitability constraints without requiring access to AI model internals or operational control over third-party systems. The analysis situates AI-mediated omission risk within established conduct-risk and suitability doctrines and clarifies the governance implications of detectability, repeatability, and foreseeability.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 25%
Ethics and Social Impacts of AI
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AI as an Attributable Representation Channel: When AI-Mediated Suitability Claims Become a Governance Failure — Tim de Rosen · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS