Research Framework
This research framework is developed as the foundational structure for a Doctorate of Business Administration (DBA) research project.
Introduction
The GAB/BAG Integrated Model is a research-driven framework designed to address governance, accountability, and decision traceability challenges in private banking environments.
This page outlines the current research status of the model, its deliberate scope, and the planned trajectory for empirical validation and future extensions.
Provisional Doctoral Research Question
Provisional Title
Decision Traceability as a Governance Infrastructure: Supporting Long-Term Institutional Defensibility in AI-Assisted Private Banking.
Doctoral Research Question
How can decision traceability be designed as a governance infrastructure—rather than a technical feature—to support long-term institutional defensibility in AI-assisted private banking decisions?
This research question frames decision traceability as an institutional and governance challenge, rather than a purely technical implementation issue, within AI-assisted private banking environments.
Research Status
All contribuThe GAB/BAG Integrated Model is currently developed as a conceptual and architectural research framework.
Its primary objective is to formalize how operational decisions can be structured, documented, and rendered traceable through the combined use of artificial intelligence and blockchain-based governance mechanisms.tions follow a consistent analytical structure and are released periodically.
Scope Delimitation
The current scope of the research deliberately focuses on internal operational decision-making processes, governance accountability, and auditability within private banking institutions.
Client-facing applications, commercial product development, and direct financial performance optimization are intentionally excluded at this stage in order to preserve analytical clarity and methodological rigor.
Validation Trajectory
Empirical validation, applied case studies, and institutional partnerships are positioned as subsequent phases of the research agenda.
These future stages aim to evaluate the model through controlled pilots, regulatory-aligned environments, and selected operational use cases once the conceptual foundations are fully stabilized.
Research Roadmap – Alignment with the Doctoral Research Question
- Phase 1 — Conceptual reframing of decision traceability as a governance infrastructure (current phase)
This phase addresses the theoretical and conceptual redefinition of decision traceability, positioning it as an institutional and governance infrastructure rather than a purely technical feature. It establishes the analytical foundations of the GAB/BAG framework.
- Phase 2 — Design of decision traceability artefacts and applied governance pilots
This phase explores how decision traceability mechanisms can be operationalised as governance artefacts within AI-assisted private banking environments, translating conceptual principles into structured, auditable decision representations.
- Phase 3 — Institutional validation and regulatory dialogue
This phase examines how governance-oriented decision traceability can support long-term institutional defensibility, through validation against regulatory expectations, governance standards, and supervisory dialogue.
- Phase 4 — Extended applications and synthesis of governance implications
This phase consolidates findings across internal decision processes and extended client-facing or financial layers, articulating a coherent governance design framework for decision traceability in AI-assisted private banking.
Expected Contributions (DBA Perspective)
This research aims to contribute to knowledge and practice by:
- Conceptual contribution:
Reframing decision traceability as a governance infrastructure rather than a purely technical feature, contributing to the literature on AI governance, decision accountability, and institutional resilience in private banking. - Managerial contribution:
Providing a structured governance-oriented design perspective to support decision accountability, auditability, and long-term institutional defensibility in AI-assisted banking operations. - Institutional and regulatory contribution:
Informing governance and supervisory dialogues by articulating how decision traceability can support regulatory expectations, institutional accountability, and defensibility over time.
Related Research Outputs
The GAB/BAG Integrated Model: A Governance Framework for AI and Blockchain in Swiss Private Banking
The GAB/BAG research program is supported by working papers and conceptual research outputs that progressively formalize the model and its theoretical foundations.
The section is intentionally moderated and does not enable public comments.
