A tailored course, built for your situation
Mastering ISO 42001 for Investment Management Practitioners
Build defensible, high-quality AI governance artefacts that stand up to internal and external scrutiny
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
Who this is for
Senior investment management professionals integrating AI governance into existing compliance and oversight frameworks
Who this is not for
Entry-level analysts, software developers focused on model build-out, or corporate trainers without domain-specific governance responsibilities
What you walk away with
- Produce complete and accurate AI governance documentation aligned with ISO 42001 on first review
- Apply investment management context to AI risk assessments with precision
- Build stakeholder-ready SoA and control implementation records without revision cycles
- Reference real-world financial services examples when shaping policy decisions
- Deploy a reusable AI governance playbook that aligns with audit and oversight expectations
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 in Financial Services
Lay the foundation for AI governance by understanding how ISO 42001 applies specifically to investment management and fiduciary oversight environments.
12 chapters in this module
- What ISO 42001 means for finance
- AI governance vs traditional compliance
- Mapping AI risks to investment decisions
- Regulatory expectations in asset management
- How Mercer uses framework alignment
- Linking AI oversight to fiduciary duty
- Key artefacts in scope
- First-party vs third-party AI use
- Governance lifecycle stages
- Stakeholder mapping for AI
- Documentation standards
- Setting quality benchmarks
Module 2. Core Structure of ISO 42001
Break down the standard into actionable components, focusing on clauses most relevant to financial decision integrity and oversight.
12 chapters in this module
- Clause 4 context of the organization
- Clause 5 leadership commitment
- Clause 6 planning AI risks
- Clause 7 support and resources
- Clause 8 operational planning
- Clause 9 performance evaluation
- Clause 10 improvement
- Annex A controls overview
- Control selection logic
- Integration with ISO 31000
- Linking to investment oversight
- Control ownership models
Module 3. AI Risk Assessment for Investment Firms
Learn to identify and prioritize AI risks specific to portfolio modeling, performance attribution, and client reporting.
12 chapters in this module
- Defining AI use cases
- Risk scoring methodology
- Bias in performance analysis
- Transparency in model outputs
- Client communication risks
- Vendor AI model oversight
- Model drift detection plans
- Human oversight thresholds
- Escalation triggers
- Scenario testing design
- Documentation templates
- Audit readiness checks
Module 4. Building the Statement of Applicability
Create a credible, justifiable SoA that aligns with investment governance standards and withstands internal audit scrutiny.
12 chapters in this module
- What belongs in the SoA
- Justification framework design
- Exclusion rationale writing
- Control implementation levels
- Linking to investment policies
- Mapping to ISO 27001 overlaps
- Version control strategy
- Stakeholder review inputs
- Consolidating feedback
- Finalizing for sign-off
- Updating across cycles
- SoA as a living document
Module 5. AI Governance Policy Development
Draft organization-specific policies that reflect both ISO 42001 requirements and investment management best practices.
12 chapters in this module
- Policy scope definition
- Leadership accountability clauses
- Roles and responsibilities
- Model approval workflows
- Client impact disclosures
- Oversight committee structure
- Model validation frequency
- Incident reporting paths
- Training requirements
- Policy review cycles
- Versioning and control
- Integration with compliance
Module 6. Control Implementation Planning
Turn high-level controls into specific, executable steps tailored to financial data handling and model governance.
12 chapters in this module
- Control 8 1 1 asset management
- Control 8 1 2 data quality
- Control 8 2 1 human oversight
- Control 8 2 2 explainability
- Control 8 3 1 fairness
- Control 8 3 2 robustness
- Control 8 4 1 transparency
- Control 8 4 2 documentation
- Control 8 5 1 accountability
- Control 8 5 2 responsibility
- Control 8 6 1 social impact
- Control 8 6 2 environmental impact
Module 7. Documentation and Record Keeping
Establish a consistent, auditable record system for AI governance activities across investment teams.
12 chapters in this module
- Document types and owners
- Retention periods
- Access controls
- Version tracking
- Audit trail design
- Metadata requirements
- Storage solutions
- Integration with SharePoint
- Searchability standards
- Review and approval logs
- Change management process
- Disaster recovery
Module 8. Internal Audit Preparation
Prepare for audit cycles with complete, logical, and defensible artefacts aligned to both ISO 42001 and investment oversight standards.
12 chapters in this module
- Audit scope definition
- Evidence collection plan
- Interview preparation
- Control testing methods
- Finding response workflow
- Management response drafting
- Remediation tracking
- Follow-up audit planning
- External auditor expectations
- Regulatory reporting alignment
- Lessons from past audits
- Continuous improvement
Module 9. Stakeholder Communication Strategy
Develop clear, confident messaging for leadership, compliance, and investment teams on AI governance initiatives.
12 chapters in this module
- Defining audience needs
- Executive summary design
- Technical briefing templates
- FAQ development
- Presentation decks
- One-pagers for committees
- Crisis communication plan
- Media inquiry protocol
- Vendor discussion guides
- Client update frameworks
- Board-level summaries
- Feedback loops
Module 10. Integration with Existing Governance
Embed ISO 42001 practices into current investment oversight, risk management, and compliance workflows.
12 chapters in this module
- Linking to SOX controls
- Overlap with GDPR
- Mapping to NIST AI RMF
- Integration with PMO
- Reporting to compliance team
- Coordination with legal
- Model validation alignment
- Portfolio review integration
- Client reporting updates
- Vendor due diligence
- Change management process
- Training rollout
Module 11. Continuous Improvement and Monitoring
Implement feedback loops and monitoring to maintain high-quality AI governance outputs over time.
12 chapters in this module
- Performance metrics
- KPIs for AI governance
- Feedback collection
- Control reviews
- Model performance alerts
- Incident tracking
- Root cause analysis
- Update triggers
- Version upgrade planning
- Technology watch process
- Benchmarking against peers
- Maturity assessment
Module 12. Implementation Playbook Delivery
Receive a tailored playbook with templates, checklists, and process flows for immediate use in your environment.
12 chapters in this module
- How to use the playbook
- Customization guidance
- Stakeholder onboarding
- Pilot program design
- Full rollout strategy
- Training session plan
- Success metrics
- Leadership reporting
- Vendor coordination
- Compliance alignment
- Audit preparation
- Sustaining momentum
Before vs. after
Before
AI governance documentation requires multiple rounds of revisions and lacks consistency across teams
After
Polished, accurate outputs are produced on the first attempt, with clear justification and stakeholder alignment
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 45 hours of self-paced learning, with flexibility to complete modules over 4-6 weeks.
If nothing changes
Continuing with ad-hoc AI governance approaches risks increased review cycles, inconsistent outputs, and potential misalignment with evolving regulatory expectations in financial services.
How this compares to the alternatives
Unlike generic compliance courses, this program is tailored to investment management specialists, with real-world examples and templates that reflect the complexity of fiduciary oversight and portfolio governance.
Frequently asked
Is this course relevant if I’m not in IT or security?
Yes. This course is designed for investment management professionals who need to govern AI use within portfolio management, performance analysis, and client reporting.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will I receive practical tools?
Yes. You'll get a hand-built implementation playbook with templates and checklists tailored to financial services governance.
$199 one-time. Approximately 45 hours of self-paced learning, with flexibility to complete modules over 4-6 weeks..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours