GLOBAL FINTECH LAB

Global Fintech Lab · Editorial policy

Clear sources. Open questions. Human judgement.

This policy guides research into the emergence of future money, the need to prepare its possible designs in advance, and the foundations, support, security and safeguards that fintech and AI in finance may provide.

Mission and content criteria

Every proposed item must identify which core research question it addresses and explain its contribution. Information gathering, analysis and sharing serve that research purpose.

Editors assess relevance, evidence quality, explanatory value, uncertainty and rights status. A market update, product announcement or technology trend needs an explicit, supported connection to future money to qualify. Popularity or novelty alone is insufficient.

Technology coverage must distinguish demonstrated capabilities from proposed uses and assess limitations, security risks and safeguards. Design studies must state objectives, assumptions, tradeoffs and unanswered questions. Well-supported counterarguments and negative findings are eligible contributions.

Inevitability as a thesis to examine

Claims that future money is necessary or inevitable must specify their meaning, conditions, reasoning and evidence. Editors should seek alternative explanations, counterevidence and the possibility that existing systems can adapt. A general argument for monetary change does not establish that any particular design or timetable is predetermined.

Factual reporting, analytical inference, scenarios and normative proposals must be clearly distinguished. Uncertainty and material evidence gaps should remain visible.

Evidence traceability

Factual claims must be linked to identifiable sources. Research records should retain the source title, author or institution, publication date where available, URL or document identifier, access date and relevant passage or location, so an editor can trace a claim to its basis.

Prefer original documents and primary evidence where available. Identify secondary reporting, conflicting findings and source limitations. Unsupported claims must be qualified, removed or held for verification; AI-generated text is not an evidentiary source.

Sources and publication rights

Check permissions and applicable reuse conditions for quotations, images, data and other third-party material. Record attribution requirements and the basis for permitted use. Access to a source does not itself grant republication rights. Unresolved rights questions block release of the affected material.

Human editorial review and release gates

TONG is the Editor-in-Chief. Before publication, each item requires human review of its mission relevance, factual support, reasoning and uncertainty, together with completed content permission and publication rights checks. The review record should identify the version reviewed, the reviewer, the date and any outstanding conditions.

A successful login, an automated check or an AI-generated draft does not approve an article. Content approval records an editorial decision only; it does not itself authorise deployment or public release. Release requires separate explicit authorisation and completion of the applicable publication gates.

AI-assisted preparation

Tools may assist with gathering, organising, analysing and drafting material. A human editor must verify source references, quotations and substantive claims, check for omissions or misleading conclusions, and record material AI assistance in the editorial record. Responsibility for publication remains with the human editor.

Corrections and withdrawals

Material errors should be corrected with a dated record explaining what changed and why. Reassess conclusions when supporting evidence changes. Content may be withdrawn when its evidence or permissions no longer support publication.

Scope

GFL content is intended for research and general information, rather than personalised financial recommendations.