GAB/BAG Integrated Governance Framework

Conceptual Framework (Pre-Empirical)

Overview

The GAB/BAG Integrated Governance Framework is a conceptual framework designed to address governance, traceability, and accountability challenges arising from the growing use of AI-assisted decision support in regulated banking operations.

As financial institutions increasingly rely on automation and advanced analytics, operational decisions become faster but also harder to explain, audit, and defend. The GAB/BAG framework proposes a structured governance logic that separates intelligence generation from decision validation, with the objective of strengthening operational resilience and institutional defensibility.

Purpose of the Framework

The framework aims to support reflection on how banks can:

• preserve accountability in AI-assisted operational workflows,
• improve traceability of decisions and controls,
• reduce operational risk linked to opaque or automated processes,
• align digital transformation initiatives with regulatory expectations.

Rather than proposing a technological solution, the framework offers a governance-oriented conceptual lens for structuring decision chains in complex, regulated environments.

Scope and Context

The GAB/BAG framework is intentionally designed for regulated financial institutions, with a particular focus on:

• banking operations (middle- and back-office),
• AI-assisted decision environments,
• operational risk governance and auditability,
• supervisory and regulatory alignment.

The framework is not intended as a generic AI model and is not sector-agnostic. Its assumptions reflect environments subject to strong regulatory oversight, internal controls, and accountability requirements.

Core Concept: Separation of Intelligence and Governance

At the heart of the framework lies a structural distinction between two complementary layers:

GAB — Generative Intelligence Layer

The GAB layer represents the intelligence dimension of the framework.

Conceptually, it focuses on interpretation, analysis, and decision support, such as:

• understanding unstructured information,
• generating recommendations or alerts,
• supporting operational workflows through reasoning and automation.

BAG — Assurance & Governance Layer

The GAB layer does not validate or authorize decisions. Its role is to assist, not to govern.

The BAG layer represents the governance and validation dimension of the framework.

It is conceptually designed to ensure:

• validation of decisions and actions,
• traceability and auditability of operational steps,
• enforcement of governance rules and control logic.

By separating governance from intelligence, the framework aims to preserve institutional accountability even in highly automated environments.

Conceptual Architecture

The GAB/BAG framework is structured as a dual-layer governance architecture:

• an intelligence layer dedicated to analysis and recommendation,
• a governance layer dedicated to validation, control, and traceability.

This separation is intended to clarify roles, responsibilities, and escalation paths within AI-assisted operational processes, while maintaining alignment with regulatory and audit expectations.

What the Framework Is — and Is Not

What it is

• A conceptual governance framework
• A methodological lens for thinking about AI-assisted operations
• A structured approach to decision traceability and accountability

What it not

• Not a software product
• Not an implementation methodology
• Not a consulting offering
• Not an empirical or performance-based study

The framework does not claim efficiency gains, risk reduction metrics, or measurable outcomes at this stage.

Research Status

The GAB/BAG Integrated Governance Framework is currently presented in a conceptual, pre-empirical stage.

It is shared to support methodological discussion and governance reflection.

Any future empirical exploration would aim to examine applicability, limitations, and governance implications and would be conducted separately, under appropriate methodological and institutional conditions.

Disclaimers & Research Status

General Disclaimer

This framework is presented for conceptual and methodological discussion only. It does not rely on proprietary data, confidential information, or internal institutional processes. No empirical validation or performance claims are made at this stage.

Research Disclaimer

The framework precedes any empirical validation. Any future empirical exploration will be conducted independently and subject to appropriate ethical and institutional considerations.

Professional Independence Disclaimer

This work is developed independently and does not represent the views, strategies, or practices of any employer or financial institution.

Non-Commercial Disclaimer

At this stage, the framework is not presented as a commercial product, service, or implementation offering.

Version

GAB/BAG Integrated Governance Framework

Version 1.0 — Conceptual (Pre-Empirical)

GAB/BAG Integrated Governance Framework

Conceptual Framework (Pre-Empirical)

Overview

The GAB/BAG Integrated Governance Framework is a conceptual framework designed to address governance, traceability, and accountability challenges arising from the growing use of AI-assisted decision support in regulated banking operations.

As financial institutions increasingly rely on automation and advanced analytics, operational decisions become faster but also harder to explain, audit, and defend. The GAB/BAG framework proposes a structured governance logic that separates intelligence generation from decision validation, with the objective of strengthening operational resilience and institutional defensibility.

Purpose of the Framework

The framework aims to support reflection on how banks can:

• preserve accountability in AI-assisted operational workflows,
• improve traceability of decisions and controls,
• reduce operational risk linked to opaque or automated processes,
• align digital transformation initiatives with regulatory expectations.

Rather than proposing a technological solution, the framework offers a governance-oriented conceptual lens for structuring decision chains in complex, regulated environments.

Scope and Context

The GAB/BAG framework is intentionally designed for regulated financial institutions, with a particular focus on:

• banking operations (middle- and back-office),
• AI-assisted decision environments,
• operational risk governance and auditability,
• supervisory and regulatory alignment.

The framework is not intended as a generic AI model and is not sector-agnostic. Its assumptions reflect environments subject to strong regulatory oversight, internal controls, and accountability requirements.

Core Concept: Separation of Intelligence and Governance

At the heart of the framework lies a structural distinction between two complementary layers:

GAB — Generative Intelligence Layer

The GAB layer represents the intelligence dimension of the framework.

Conceptually, it focuses on interpretation, analysis, and decision support, such as:

• understanding unstructured information,
• generating recommendations or alerts,
• supporting operational workflows through reasoning and automation.

BAG — Assurance & Governance Layer

The GAB layer does not validate or authorize decisions. Its role is to assist, not to govern.

The BAG layer represents the governance and validation dimension of the framework.

It is conceptually designed to ensure:

• validation of decisions and actions,
• traceability and auditability of operational steps,
• enforcement of governance rules and control logic.

By separating governance from intelligence, the framework aims to preserve institutional accountability even in highly automated environments.

Conceptual Architecture

The GAB/BAG framework is structured as a dual-layer governance architecture:

• an intelligence layer dedicated to analysis and recommendation,
• a governance layer dedicated to validation, control, and traceability.

This separation is intended to clarify roles, responsibilities, and escalation paths within AI-assisted operational processes, while maintaining alignment with regulatory and audit expectations.

What the Framework Is — and Is Not

What it is

• A conceptual governance framework
• A methodological lens for thinking about AI-assisted operations
• A structured approach to decision traceability and accountability

What it not

• Not a software product
• Not an implementation methodology
• Not a consulting offering
• Not an empirical or performance-based study

The framework does not claim efficiency gains, risk reduction metrics, or measurable outcomes at this stage.

Research Status

The GAB/BAG Integrated Governance Framework is currently presented in a conceptual, pre-empirical stage.

It is shared to support methodological discussion and governance reflection.

Any future empirical exploration would aim to examine applicability, limitations, and governance implications and would be conducted separately, under appropriate methodological and institutional conditions.

Disclaimers & Research Status

General Disclaimer

This framework is presented for conceptual and methodological discussion only. It does not rely on proprietary data, confidential information, or internal institutional processes. No empirical validation or performance claims are made at this stage.

Research Disclaimer

The framework precedes any empirical validation. Any future empirical exploration will be conducted independently and subject to appropriate ethical and institutional considerations.

Professional Independence Disclaimer

This work is developed independently and does not represent the views, strategies, or practices of any employer or financial institution.

Non-Commercial Disclaimer

At this stage, the framework is not presented as a commercial product, service, or implementation offering.

Version

GAB/BAG Integrated Governance Framework

Version 1.0 — Conceptual (Pre-Empirical)