Threat Analytics Across Payment Products: Evidence Requirements for Agent Investigations

Preprint, not peer reviewed. Abuse of a payment platform can cross products and accounts, and the platform's own protective decisions change which outcomes can later be observed. A blocked payment cannot produce a chargeback; an incomplete search cannot establish absence; a reused conclusion cannot corroborate itself. This paper specifies the records an AI agent needs in order to investigate such cases under human authority. The specification rests on three requirements. First, each outcome record links to the control decision that may have shaped it, with separate fields for reporting delay, outcomes the decision made unobservable, and false reports. Second, a gateway outside the agent records what each query actually covered, and every fact retains both the time it happened and the time the system learned it. Third, a person must release a conclusion before it enters organizational memory for reuse by later investigations; a released conclusion serves only as a hypothesis or context, and any record that an agent output informed must link back to that output. The specification connects these requirements to 71 signals, the kinds of records an investigator can check, and 24 responsibilities for investigation, review and reuse. Public sources supply the design premises, and Stripe's public product pages and documentation provide an illustrative product scope. Two hypothetical investigations show how missing context changes the conclusions that the same observations can support, and an evaluation plan proposes tests of evidential quality, operational cost and agent benefit. The contribution is a joint specification for investigation across payment products, built on established methods and recent agent-governance designs. It is a synthesis, not a new method or a measured result: the specification has not been built or evaluated, and no practitioner has reviewed it. The record includes the supplement, its 19 data files, the references and the build and check scripts.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-29
DOI
https://doi.org/10.5281/zenodo.23772005
Primary Topic
Ethics and Social Impacts of AI
Type
preprint
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preprint

Threat Analytics Across Payment Products: Evidence Requirements for Agent Investigations

Jonathan Matkowsky
3 links
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
preprint

Threat Analytics Across Payment Products: Evidence Requirements for Agent Investigations

Jonathan Matkowsky
preprint en

Abstract

Preprint, not peer reviewed. Abuse of a payment platform can cross products and accounts, and the platform's own protective decisions change which outcomes can later be observed. A blocked payment cannot produce a chargeback; an incomplete search cannot establish absence; a reused conclusion cannot corroborate itself. This paper specifies the records an AI agent needs in order to investigate such cases under human authority. The specification rests on three requirements. First, each outcome record links to the control decision that may have shaped it, with separate fields for reporting delay, outcomes the decision made unobservable, and false reports. Second, a gateway outside the agent records what each query actually covered, and every fact retains both the time it happened and the time the system learned it. Third, a person must release a conclusion before it enters organizational memory for reuse by later investigations; a released conclusion serves only as a hypothesis or context, and any record that an agent output informed must link back to that output. The specification connects these requirements to 71 signals, the kinds of records an investigator can check, and 24 responsibilities for investigation, review and reuse. Public sources supply the design premises, and Stripe's public product pages and documentation provide an illustrative product scope. Two hypothetical investigations show how missing context changes the conclusions that the same observations can support, and an evaluation plan proposes tests of evidential quality, operational cost and agent benefit. The contribution is a joint specification for investigation across payment products, built on established methods and recent agent-governance designs. It is a synthesis, not a new method or a measured result: the specification has not been built or evaluated, and no practitioner has reviewed it. The record includes the supplement, its 19 data files, the references and the build and check scripts.

Zenodo (CERN European Organization for Nuclear Research)
Peace, justice, and strong institutions
Ethics and Social Impacts of AI
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Threat Analytics Across Payment Products: Evidence Requirements for Agent Investigations — Jonathan Matkowsky · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS