If you are a compliance officer, risk manager, or technology governance lead at a financial institution or critical infrastructure provider in Latin America, this playbook was built for you.
Financial institutions and regulated technology providers across Latin America face increasing scrutiny over the ethical deployment, oversight, and risk management of artificial intelligence systems. With regional data protection authorities adopting stricter interpretations of algorithmic transparency and accountability, and international standards like ISO/IEC 42001 setting new benchmarks for AI governance, your team must demonstrate structured control over both internal AI applications and third-party AI vendors. The absence of a formal AI management system exposes your organization to regulatory penalties, reputational damage, and operational disruption, especially when AI systems influence credit decisions, fraud detection, customer service automation, or risk modeling.
Engaging external consultants from global firms to design an AI governance framework typically costs between EUR 80,000 and EUR 250,000. Alternatively, dedicating internal resources requires at least 3 full-time staff over 4 to 6 months to research standards, draft policies, align controls, and prepare for audit readiness. This playbook delivers the same structured output for a one-time cost of $395, providing immediate, actionable documentation that accelerates implementation without reliance on costly consultants or prolonged internal effort.
What you get
| Phase | File Type | Description | Quantity |
| Foundation | Domain Assessments | Structured self-assessment tools covering each of the seven domains of AI governance under ISO/IEC 42001, with 30 targeted questions per domain to evaluate current maturity and identify gaps | 7 |
| Design | Evidence Collection Runbook | Step-by-step guide detailing what evidence to gather, from which departments, and in what format to support each control requirement across ISO/IEC 42001 and mapped frameworks | 1 |
| Implementation | RACI Templates | Pre-built responsibility assignment matrices defining roles for AI policy ownership, risk assessment, vendor oversight, incident response, and executive review | 1 |
| Implementation | Work Breakdown Structure (WBS) Template | Hierarchical task list for implementing an AI management system, broken into phases, deliverables, and accountable units with estimated timelines | 1 |
| Validation | Audit Prep Playbook | Comprehensive checklist and preparation guide for internal or third-party audits against ISO/IEC 42001, including document retention schedules, interview preparation notes, and evidence submission protocols | 1 |
| Integration | Cross-Framework Mappings | Detailed matrix linking ISO/IEC 42001 controls to NIST AI RMF, COBIT 2019, and CRISC to enable alignment with existing governance programs and reduce duplication | 1 |
| Supplemental | AI Third-Party Risk Assessment Workbook | Sample chapter featuring a 30-question assessment tool for evaluating AI vendors on data ethics, model transparency, security practices, contractual obligations, and regional compliance | 1 |
| Total Files | 64 | ||
Domain assessments
The seven domain assessments included in this playbook provide granular evaluation tools across core areas of AI governance. Each contains 30 questions designed to benchmark current practices, identify control gaps, and prioritize remediation actions:
- Leadership and Accountability: Evaluates executive oversight, governance structure, and documented responsibility for AI system outcomes.
- Risk Management: Assesses processes for identifying, classifying, and mitigating AI-related risks including bias, inaccuracy, and unintended consequences.
- Data Governance: Reviews data sourcing, quality assurance, privacy compliance, and lifecycle management for AI training and inference.
- Model Development and Deployment: Examines model design standards, testing protocols, version control, and deployment approvals.
- Monitoring and Performance: Measures ongoing tracking of AI system behavior, drift detection, and feedback integration.
- Transparency and Explainability: Tests documentation practices, stakeholder communication, and explainability mechanisms for regulated decisions.
- Vendor and Third-Party Oversight: Focuses on due diligence, contract terms, audit rights, and performance monitoring for external AI providers.
What this saves you
| Activity | Traditional Approach | With This Playbook |
| Develop AI governance framework from scratch | 6, 9 months of internal effort; multiple consultant workshops | Framework foundation established in 2, 3 weeks using templates |
| Map ISO/IEC 42001 to internal controls | Manual analysis across departments; high risk of misalignment | Pre-built cross-mappings to NIST AI RMF, COBIT 2019, CRISC included |
| Prepare for AI system audit | Ad hoc evidence collection; last-minute scrambling | Evidence runbook and audit prep playbook streamline readiness |
| Assess third-party AI vendors | Custom questionnaires developed per vendor; inconsistent criteria | Standardized 30-question workbook ensures uniform evaluation |
| Assign roles and responsibilities | Ambiguity leads to gaps in ownership and escalation | Pre-defined RACI templates clarify accountability across functions |
Who this is for
- Compliance officers at banks, insurance companies, and payment institutions implementing AI systems under regional regulatory supervision
- Chief Risk Officers overseeing algorithmic risk in lending, fraud detection, or customer segmentation models
- Technology governance leads in fintech platforms deploying AI for automated decision-making
- Data protection officers ensuring AI applications comply with local data privacy laws and international standards
- Internal audit teams preparing to assess AI governance maturity and control effectiveness
- Legal and procurement teams managing contracts with AI vendors requiring enforceable accountability clauses
- Public sector technology directors responsible for ethical AI deployment in financial oversight or citizen services
Cross-framework mappings
This playbook includes full alignment between ISO/IEC 42001 and the following governance, risk, and control frameworks:
- ISO/IEC 42001 , Artificial Intelligence Management System
- NIST AI Risk Management Framework (AI RMF)
- COBIT 2019 , Governance and Management of Enterprise IT
- CRISC , Certified in Risk and Information Systems Control
What is NOT in this product
- This is not a software tool or platform; it does not include automated monitoring, AI model scanning, or real-time compliance dashboards
- No legal advice is provided; users are responsible for validating content against local regulations in their jurisdiction
- The templates are not pre-filled with organizational data; implementation requires internal input and customization
- It does not include training sessions, consulting hours, or direct support from the seller
- No certification body endorsement or official audit status is conferred by use of this playbook
- It does not cover non-financial sector use cases such as healthcare, education, or defense
- Translations into Portuguese or regional Spanish variants are not included; all materials are in standard English
Lifetime access and satisfaction guarantee
You receive lifetime access to the playbook with no subscription fee and no login portal. Once downloaded, the files are yours to use, modify, and distribute within your organization. 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 building practical governance tools for regulated industries, analyzing 692 international compliance frameworks and establishing 819,000+ cross-framework mappings. Their resources are used by more than 40,000 practitioners across 160 countries, focusing on delivering structured, implementable guidance for risk, compliance, and audit professionals in highly supervised environments.
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.
