A tailored course, built for your situation
Mastering IFRS 17 for Data Engineers in Financial Services
Implement and govern IFRS 17-compliant data frameworks with precision and cross-functional reach
$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.
Technical data engineers are now expected to align with high-stakes financial reporting standards, but most lack structured guidance on IFRS 17 implementation at the data layer.
The situation this course is for
IFRS 17 compliance requires more than accurate models, it demands traceable, auditable, and interpretable data pipelines that cross engineering, actuarial, and reporting boundaries. Engineers who can bridge these silos are rare, and those who do are quietly shaping the future of financial reporting.
Who this is for
Data Engineer in a financial institution, working at the intersection of data systems, actuarial models, and regulatory compliance, with growing responsibility for IFRS 17 data readiness.
Who this is not for
This course is not for auditors, accountants, or actuaries looking for policy-level guidance. It’s also not for engineers working outside financial services or those not involved in IFRS 17 data pipeline design.
What you walk away with
- Design IFRS 17-compliant data models aligned with LDT and PV calculations
- Produce audit-ready lineage documentation for key data transformations
- Coordinate with actuarial and finance teams using standardized data artifacts
- Implement governance workflows that scale across lines of business
- Reduce rework by baking compliance requirements into early-stage data architecture
The 12 modules (with all 144 chapters)
Module 1. Understanding IFRS 17 Data Requirements
Break down the standard's data implications beyond accounting, focus on granularity, time horizons, and model inputs.
12 chapters in this module
- IFRS 17 scope as it impacts data engineering
- Liability for Remaining Coverage (LRC)
- Contractual Service Margin (CSM) pipeline needs
- Present Value of Intrinsic Options and Guarantees
- Discounting and yield curve data feeds
- Granularity rules for cohort-level reporting
- Data retention for multi-year simulations
- Aggregation paths from transaction to report
- Actuarial model dependencies
- Policy count thresholds for segmentation
- Sensitivity testing data design
- Version control for assumption inputs
Module 2. Data Modeling for Insurance Contracts
Build entity-relationship models that reflect IFRS 17’s contract boundaries and measurement principles.
12 chapters in this module
- Identifying distinct insurance contracts
- Modifications vs. cancellations
- Coverage units and duration tracking
- Allocation of acquisition costs
- Fronting vs. reinsurer relationships
- Time slicing and duration buckets
- Grouping rules for reporting units
- CSM amortization tracking fields
- Loss components and recognition timing
- Risk adjustment for non-financials
- Currency translation layers
- Policy-level vs. portfolio views
Module 3. Pipeline Architecture for LDT and PV
Engineer scalable workflows that generate Liability for Remaining Coverage and Present Value outputs with traceability.
12 chapters in this module
- LDT calculation inputs
- PV of future cash flows pipeline
- Yield curve ingestion workflows
- Inflation index data integration
- Survival probability sourcing
- Sensitivity scenario branching
- Monte Carlo output formatting
- Simulation run metadata
- Cash flow timing alignment
- Discount margin processing
- Non-recoverable CSM flags
- Interim cohort adjustments
Module 4. Governance and Audit Readiness
Structure data systems for internal and external scrutiny under IFRS 17.
12 chapters in this module
- Data lineage for compliance audits
- Versioned assumption repositories
- Change control for model inputs
- Automated reconciliation points
- Audit log schema design
- Access control for sensitive assumptions
- Documentation templates for reviewers
- Data quality checks at ingestion
- Null value handling in actuarial feeds
- Reprocessing triggers and controls
- Sign-off workflows for data packages
- Cross-team review cycles
Module 5. Cross-Functional Data Collaboration
Align engineering outputs with actuarial, finance, and risk reporting needs.
12 chapters in this module
- Actuarial data request patterns
- Shared schema conventions
- Common calendar for runs
- Data dictionary ownership
- Staging area protocols
- Feedback loops from actuarial review
- Error classification and routing
- Priority tagging for urgent fixes
- Documentation for non-engineers
- Glossary alignment with accounting
- Meeting rhythm integration
- Shared tooling for data validation
Module 6. Automation and Scalability
Design systems that scale across products, regions, and reporting cycles.
12 chapters in this module
- Template-based pipeline generation
- Region-specific discounting rules
- Product-onboarding checklists
- Batch scheduling for quarter-end
- Parallel run coordination
- Error retry mechanisms
- Monitoring for CSM drift
- Alert thresholds for anomalies
- Pipeline rollback design
- Data packaging for export
- Compression and storage strategy
- Scalable indexing for retrieval
Module 7. IFRS 17 and Local GAAP Integration
Handle data needs for dual reporting under IFRS 17 and US GAAP.
12 chapters in this module
- Differences in liability measurement
- Data segregation strategies
- Reconciliation data points
- Dual output formatting
- Tax jurisdiction tagging
- Local statutory adjustments
- Currency reporting thresholds
- Regulatory vs. internal views
- Run logic branching
- Data masking for GAAP-only fields
- Audit boundary definition
- Cross-reporting consistency checks
Module 8. Reinsurance and Fronting Arrangements
Structure data systems to reflect reinsurance contracts and fronting complexity.
12 chapters in this module
- Identifying reinsured contracts
- Fronting fee allocation
- Risk transfer validation data
- Reinsurance recoverables tracking
- Collateral data fields
- Duration matching checks
- Ceded vs. net liability views
- Reinsurance profit recognition
- Contractual modifications
- Reinstatement clauses data
- Reporting to cedants
- Audit trails for cessions
Module 9. Data Quality and Validation
Implement checks that prevent errors from propagating into regulatory reports.
12 chapters in this module
- Range checks for assumptions
- Cohort-level consistency rules
- CSM sign validation
- PV monotonicity checks
- Currency balance validations
- Cash flow sign rules
- Survival probability bounds
- Discount margin reasonableness
- Policy count reconciliation
- Migration data verification
- Backward compatibility rules
- Automated anomaly detection
Module 10. Technology Stack Integration
Integrate IFRS 17 pipelines with existing data platforms and systems.
12 chapters in this module
- Snowflake schema patterns
- Databricks pipeline orchestration
- Azure Data Factory integration
- Power BI dashboards for finance
- SAP actuarial input feeds
- Oracle general ledger alignment
- API design for actuarial calls
- Metadata tagging standards
- Data catalog integration
- CI/CD for data changes
- Containerization of runs
- Infrastructure-as-code templates
Module 11. Change Management and Release Cycles
Coordinate updates across teams and systems without disrupting compliance.
12 chapters in this module
- Quarterly assumption update cycle
- Versioning for regulatory submissions
- Backward compatibility planning
- Stakeholder notification patterns
- Rollout to actuarial teams
- Finance data freeze periods
- Emergency patch protocols
- Documentation change tracking
- Impact assessment workflows
- Legacy data sunsetting
- User acceptance testing
- Post-release validation
Module 12. Future-Proofing and Regulatory Evolution
Prepare for upcoming changes to IFRS 17 implementation and enforcement.
12 chapters in this module
- IASB amendment tracking
- Jurisdiction-specific guidance
- Local regulator expectations
- Data retention law changes
- ESG-linked reporting overlaps
- Climate risk scenario integration
- Digital reporting formats
- XBRL tagging readiness
- Audit trail expansion
- Public disclosure data layers
- Stakeholder communication updates
- Internal training materials
How this maps to your situation
- Actuarial data handoff
- Quarter-end reporting cycle
- Regulatory audit preparation
- Cross-functional project rollout
Before vs. after
Before
Working on IFRS 17 data pipelines without structured guidance, leading to rework and misalignment with actuarial and finance teams.
After
Confidently designing and governing IFRS 17-compliant data systems that are audit-ready and scalable across business units.
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 access.
Time investment: Approximately 3 hours per module, designed to fit around core responsibilities, total time investment around 36 hours over 6-8 weeks.
If nothing changes
Continuing without a structured approach risks data misalignment, audit findings, and repeated fixes across teams, costing time and credibility.
How this compares to the alternatives
Unlike generic IFRS 17 courses focused on accounting, this course is built specifically for data engineers. It skips theory and focuses on implementable data design, pipeline patterns, and governance workflows used in real financial institutions.
Frequently asked
Is this course suitable for non-actuarial engineers?
Yes, it's designed for data engineers in financial services who support IFRS 17 reporting but are not actuaries or accountants.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Do I need prior IFRS 17 experience?
No, this course starts with fundamentals and builds to advanced implementation patterns.
$199 one-time. Approximately 3 hours per module, designed to fit around core responsibilities, total time investment around 36 hours over 6-8 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