FRN research report
Assessing claims made by AI trading platforms
A research framework for examining automated investment claims, platform records and the limits of public information.
Published 24 September 2026 · Prepared by Fraud Response Network
Scope: this publication is a research framework. It does not report a client investigation or make claims about a named firm or case.
This report sets out questions an investigator can use when reviewing a platform that attributes performance to artificial intelligence or automated trading. It is a research framework, not a finding about a named service or an empirical claim about prevalence.
Separate the claim from the evidence
Marketing language, a displayed balance and a chart are statements made by the platform. They do not independently establish that a trade occurred, that an asset is held or that the displayed amount can be withdrawn. A review should identify each claim, the record that might corroborate it and the evidence still missing.
Map the service and its operators
Record the exact domain, legal entity, claimed address, payment routes, app publisher and stated custody arrangements. Compare these details against official registers and public company records using sources reached independently. A name match alone is not proof that the registered entity operates the website.
Examine the account and payment trail
Preserve account exports, deposit instructions, transaction receipts, withdrawal requests and communications. Distinguish payments to a platform from payments to separate beneficiaries. Where blockchain activity is involved, transaction records can show ledger movement; linking an address to a person requires separate corroboration.
Limits and responsible conclusions
Access may be unavailable, records may be incomplete, and public technical data may be shared or change over time. A useful report describes those gaps and alternative explanations. This framework does not estimate loss, identify a specific operator or predict recovery.