The DFAS-FEP Protocol: A Global Governance Standard for Responsible AI Use and Authorship Integrity in Financial Modelling

Abstract

This paper proposes the first structured global doctrine for responsible authorship in AI-assisted financial modelling. Grounded in the emerging scientific discipline of Dynamic Financial Applied Science (DFAS), the DFAS-FEP (Future Engine Prototype) Protocol introduces a replicable classification system that distinguishes human-authored models, AI-assisted outputs, and unvalidated AI-generated logic. The protocol provides clear disclosure guidelines, validation thresholds, and a multiclass taxonomy (Class I–IV), enabling researchers to address a growing governance gap in AI-augmented financial research.

Rather than restricting innovation, DFAS reframes transparency as a competitive advantage. The paper outlines practical implementation strategies, strategic use cases, and enforcement templates designed for academic institutions, journals, and research centres. By codifying the principle that AI may assist (but must not author), the DFAS-FEP Protocol establishes itself as a future-proof standard for intellectual integrity in AI-integrated model authorship.

DFAS redefines AI as a renewable, ethically governed asset, regulated, traceable, and transparent rather than an epistemic threat. In doing so, it contributes to the broader discourse on responsible AI use in research, aligning with global calls for AI governance (Floridi & Cowls, 2021; OECD, 2023).

The DFAS-FEP Protocol extends the foundational logic of the DFAS doctrine (Alaali, forthcoming), which codifies forward-looking financial intelligence and authorship integrity in model development. DFAS-FEP stands to become the first globally recognized governance protocol for AI-authored models in finance, and potentially a cross-disciplinary standard for research authorship in the AI era.

Keywords: Hasan Alaali, AIA, CPA, IPA Fellow Member, DFAS, Dynamic financial applied science, AI Governance, Authorship Integrity, Financial Modelling, DFAS-FEP Protocol, Responsible AI Use, Future Engine Prototypes, Model Validation, Scientific Transparency, Intelligent Finance, AI Disclosure Standards

JEL Classification: C63, C88, D83, G17, K24, O33, M48, I23