If you are a Data Governance Lead, Chief Data Officer, or AI Ethics Officer at a regulated financial institution, this playbook was built for you.
As a senior data or AI governance professional in financial services, you face mounting pressure to align emerging technology use with strict regulatory expectations. Supervisory bodies now require documented governance over AI systems and data assets, with clear accountability, risk classification, and audit trails. You must demonstrate compliance with international standards while enabling innovation in a high-stakes environment where model opacity, data lineage gaps, and ethical concerns can trigger regulatory scrutiny. Without a structured, board-ready framework, your team risks reactive firefighting instead of strategic governance.
Developing an internal governance framework from scratch typically requires engagement with a Big-4 advisory firm at a cost between EUR 80,000 and EUR 250,000. Alternatively, assembling an internal task force of 3 to 5 full-time staff over 4 to 6 months demands significant opportunity cost and coordination overhead. This playbook delivers the same foundational structure, control mappings, and implementation tools at a fraction of the cost, just $395.
What you get
| Phase | File Type | Description | File Count |
| Assessment | Domain Assessment | 30-question evaluation covering governance, risk, ethics, metadata, data quality, AI lifecycle, and compliance alignment. Each mapped to ISO 38505 and NIST AI RMF control objectives. | 7 |
| Evidence Collection | Runbook | Step-by-step guide for gathering and organizing documentation required for internal audits and regulator requests. Includes file naming conventions, retention rules, and stakeholder interview templates. | 1 |
| Audit Preparation | Playbook | Checklist-driven process for responding to audit findings, scheduling control testing, and preparing executive summaries for board reporting. | 1 |
| Implementation | RACI Template | Pre-built responsibility assignment matrix for data governance roles across business units, IT, compliance, and risk functions. Customizable for institution size and structure. | 1 |
| Implementation | Work Breakdown Structure (WBS) | Hierarchical task list for launching a data and AI governance program, including milestones, dependencies, and estimated effort per activity. | 1 |
| Mapping | Cross-Framework Matrix | Comprehensive spreadsheet linking ISO 38505 clauses, NIST AI RMF subcategories, COBIT 2019 practices, and GDPR Articles to common control statements and implementation guidance. | 1 |
| Guidance | Implementation Handbook | Narrative guide explaining how to sequence activities, interpret assessment results, and integrate governance into existing data office workflows. | 1 |
| Tools | Excel & Word Templates | Editable templates for policy drafting, risk registers, AI inventory logs, and data classification matrices. | 51 |
| Total Files | 64 | ||
Domain assessments
Each of the seven domain assessments contains 30 targeted questions designed to evaluate maturity and identify control gaps. They are:
- Data Governance Structure: Evaluates the existence and effectiveness of governance bodies, charters, decision rights, and escalation paths for data and AI initiatives.
- AI Risk Management: Assesses alignment with NIST AI RMF functions (Govern, Map, Measure, Manage) across model development, deployment, and monitoring.
- Ethical AI Principles: Reviews institutional adherence to fairness, transparency, accountability, and human oversight in AI applications.
- Metadata and Lineage: Measures completeness of technical and business metadata, data provenance tracking, and integration with cataloging tools.
- Data Quality Management: Tests processes for defining, monitoring, and improving data accuracy, completeness, consistency, and timeliness.
- Stakeholder Engagement: Gauges communication effectiveness between data offices, legal, compliance, risk, and business units on governance matters.
What this saves you
| Activity | Without This Playbook | With This Playbook |
| Develop assessment framework | 80, 120 hours of internal legal, compliance, and data office time | Use pre-built 30-question assessments (7 domains) |
| Map controls across standards | Manual comparison of ISO 38505, NIST AI RMF, COBIT, GDPR (60+ hours) | Use provided cross-framework matrix (ready to import) |
| Prepare for audit | Ad hoc evidence gathering, inconsistent formatting, rework | Follow evidence runbook and audit prep playbook |
| Assign responsibilities | Prolonged workshops to define RACI across silos | Adapt pre-built RACI template to your organization |
| Plan implementation | Unstructured rollout with missed dependencies and delays | Execute from detailed WBS with phased milestones |
| Document policies | Draft from scratch using external templates with compliance gaps | Customize editable policy and register templates |
Who this is for
- Chief Data Officers building a formal governance function in a financial institution subject to supervisory review
- Data Governance Managers tasked with implementing ISO 38505 or responding to AI governance mandates
- AI Risk Leads establishing controls over machine learning models in credit scoring, fraud detection, or customer service
- Compliance Officers needing to demonstrate alignment between data practices and regulatory expectations
- Internal Audit Teams preparing to assess data and AI governance maturity
- Legal Counsel responsible for AI ethics policies and regulatory disclosures
- Technology Risk Managers integrating AI oversight into enterprise risk frameworks
Cross-framework mappings
This playbook provides direct control mappings across the following frameworks:
- ISO/IEC 38505-1:2017 (Governance of Data for Information Technology)
- ISO/IEC 38505-2:2018 (Guidance on Data Governance)
- NIST AI Risk Management Framework (AI RMF 1.0)
- COBIT 2019 (Focus areas: DSS04, DSS05, DSS06, APO12, BAI09)
- General Data Protection Regulation (GDPR) , Articles 5, 13, 14, 15, 21, 22, 25, 35
What is NOT in this product
- This is not a software tool or SaaS platform. It does not include automated scanning, AI model monitoring, or data catalog integration.
- It does not provide legal advice or substitute for counsel. Users are responsible for adapting content to their jurisdiction and institutional context.
- No third-party licenses are included. You must secure access to any external systems referenced (e.g., data quality tools, metadata repositories).
- It does not cover non-financial sector use cases such as healthcare, retail, or public sector education.
- There are no training videos, live workshops, or consulting hours included in the base purchase.
- It does not include sector-specific model risk management templates beyond those applicable to AI governance under NIST AI RMF.
Lifetime access and satisfaction guarantee
You receive lifetime access to all 64 files with no subscription and no login portal. Download the materials once and retain them indefinitely. If this playbook does not save your team at least 100 hours of manual compliance work, email us for a full refund. No questions, no friction.
About the seller
The creator has spent 25 years developing governance frameworks for regulated industries. They have analyzed 692 compliance and risk management frameworks and built 819,000+ cross-framework mappings. Their tools are used by 40,000+ practitioners across 160 countries, including professionals in banking, insurance, asset management, and financial market infrastructure.
Need this for your team? We offer site licenses starting at $2,500 for up to 25 users. Reply to this page or DM Gerard directly on LinkedIn.
