A tailored course, built for your situation
Mastering Basel III for Senior BI Developers in Financial Services
Turn regulatory capital rules into actionable data models with precision
$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 BI developer in financial services with direct input into risk data pipelines and regulatory capital reporting
Who this is not for
Entry-level analysts, non-technical compliance staff, or professionals outside financial data infrastructure
What you walk away with
- Produce capital adequacy models that align with Basel III standardized measurement templates
- Build traceable data flows from source systems to regulatory outputs
- Confidently own the logic behind leverage ratio and capital conservation buffers
- Deliver auditable BI layers that reduce follow-up questions from risk teams
- Gain recognition as the internal subject-matter owner on Basel-linked data design
The 12 modules (with all 144 chapters)
Module 1. Basel III Fundamentals for Data Practitioners
Ground your work in the actual pillars of Basel III , scope, capital tiers, and minimum requirements , tailored to how BI systems interpret them.
12 chapters in this module
- Understanding Basel III’s three pillars in data context
- Mapping Tier 1 vs Tier 2 capital in source systems
- How leverage ratio differs from risk-weighted assets
- Locating capital floor triggers in daily reporting
- Translating regulatory buffers into data thresholds
- Key differences between Basel II.5 and III
- Role of the Internal Capital Adequacy Assessment Process
- Impact of output floor rules on model design
- Treatment of counter-cyclical capital buffers
- Linking PILLAR 2 Review outcomes to data quality
- Identifying which exposures require Standardized Approach
- Overview of the Fundamental Review of the Trading Book
Module 2. Data Architecture for Risk-Weighted Assets
Design pipelines that accurately assign risk weights to exposures across asset classes using Basel-prescribed methodologies.
12 chapters in this module
- Categorizing exposures by asset class for weighting
- Mapping sovereign vs corporate credit risk treatment
- Residential mortgage risk weighting logic
- Handling exposures to unregulated financial entities
- Applying large exposure regime thresholds
- Incorporating credit conversion factors for derivatives
- Treatment of OTC derivatives collateralization
- Data fields required for CCR capital charge
- Segregating trading book vs banking book exposures
- Validating 150% floor for unrecognized entities
- Modeling treatment of equity exposures
- Building fallback logic for missing risk parameters
Module 3. Leverage Ratio Data Pipeline Design
Construct robust, auditable data layers that feed into the leverage ratio calculation without overstating exposure.
12 chapters in this module
- Defining on-balance sheet exposure for leverage
- Treatment of off-balance sheet items in Basel III
- Double counting rules in derivative netting
- Deriving exposure value from notional amounts
- Application of simple input approach for derivatives
- Validating recognition of central counterparty exposure
- Data logic for repo-style transactions
- Treatment of gold and precious metal exposures
- Handling unsettled securities transactions
- Adjusting for eligible hedges in repo markets
- Identifying excluded assets from leverage base
- Documenting data assumptions for auditor review
Module 4. Standardized vs Internal Models Data Flow
Separate data paths for standardized approach and internal models, ensuring clarity where regulatory discretion applies.
12 chapters in this module
- Determining when SA is mandatory
- Validating input data for IRB models
- Documenting model eligibility criteria in ETL
- Flagging portfolios requiring supervisory slotting
- Data requirements for foundation IRB treatment
- Advanced IRB inputs for PD, LGD, and EAD
- Handling migration from foundation to advanced
- Building fallback pipelines for model rejection
- Auditing model boundary conditions in staging
- Linking stress testing data to internal models
- Managing model waiver expirations in flow
- Versioning model logic updates in data layer
Module 5. Output Floor Implementation Logic
Embed floor rules into data workflows so modelled results never fall below standardized minimums.
12 chapters in this module
- Understanding 72.5% output floor mechanics
- Timing of floor application in reporting cycle
- Building dual-track calculation pipelines
- Validating floor impact by business unit
- Data tagging for floor-triggered accounts
- Adjusting for portfolio-level vs transaction-level
- Documentation needs for floor overrides
- Reconciling floor-adjusted vs raw outputs
- Feeding floor results into capital planning
- Tracking historical floor variance trends
- Alerting on near-floor model behaviour
- Reporting floor impact to internal risk committees
Module 6. Capital Conservation Buffer Data Logic
Model buffer impacts and build early warning systems based on capital ratio trends.
12 chapters in this module
- Defining the conservation buffer ratio ranges
- Linking buffer status to dividend policy data
- Modelling buffer impact on capital distribution
- Tracking capital ratio trends over time
- Setting thresholds for automated alerts
- Feeding buffer data into strategic planning
- Differentiating buffer vs countercyclical
- Calculating minimum distribution limits
- Integrating buffer status with scenario models
- Documentation for buffer-related decisions
- Reconciling buffer logic across subsidiaries
- Versioning buffer rule changes in data
Module 7. Data Lineage for Regulatory Audit Trails
Ensure full traceability from raw data to Basel-compliant outputs using structured metadata and tagging.
12 chapters in this module
- Defining critical data elements for Basel
- Tagging data origin in ingestion layer
- Mapping transformation logic across stages
- Building automated lineage documentation
- Using metadata to justify assumptions
- Validating data ownership at each node
- Linking controls to data touchpoints
- Integrating lineage with GRC platforms
- Testing reproducibility of final outputs
- Documenting exception handling procedures
- Preparing lineage for on-site inspections
- Training auditors on data flow maps
Module 8. Automated Validation Rules for Basel Inputs
Implement data quality checks that prevent invalid inputs from entering Basel calculation pipelines.
12 chapters in this module
- Validating credit rating mappings in source
- Checking risk weight boundaries at ingestion
- Flagging missing collateral values
- Enforcing currency conversion accuracy
- Monitoring exposure date consistency
- Detecting stale customer risk ratings
- Rejecting unapproved model inputs
- Validating counterparty eligibility for netting
- Testing fallback logic for missing data
- Benchmarking input completeness over time
- Alerting on threshold breaches in real-time
- Logging validation decisions for audit
Module 9. Cross-Border Data Aggregation Challenges
Handle jurisdictional differences in Basel implementation while maintaining global consistency.
12 chapters in this module
- Identifying local regulatory overlays on Basel
- Mapping home vs host country requirements
- Handling USS vs EU Basel interpretation gaps
- Aggregating data under different accounting rules
- Dealing with currency translation layers
- Aligning risk buckets across regions
- Validating local sign-off data needs
- Building reconciliation logic for global reports
- Managing subsidiary-level exceptions
- Documenting rationale for each variance
- Integrating with centralized risk data warehouse
- Ensuring compliance with local data sovereignty laws
Module 10. Stress Testing Data Integration
Align stress testing data pipelines with Basel III capital resilience expectations.
12 chapters in this module
- Sourcing macroeconomic scenarios for testing
- Mapping baseline vs adverse conditions
- Feeding stress results into capital planning
- Validating loan portfolio sensitivity inputs
- Modeling unemployment impact on defaults
- Integrating market shock assumptions
- Building reverse stress testing logic
- Linking stress outcomes to buffer usage
- Testing data pipeline speed under stress
- Documenting scenario assumptions clearly
- Reconciling stress results across models
- Preparing data packages for regulator review
Module 11. Vendor and Outsourcing Data Governance
Maintain control over third-party contributions to Basel-compliant data systems.
12 chapters in this module
- Defining data ownership in vendor contracts
- Auditing third-party transformation logic
- Validating outsourced model inputs
- Monitoring SLAs for data delivery timing
- Building fallbacks for vendor outages
- Documenting data handoff protocols
- Assessing vendor model risk exposure
- Integrating vendor data into central warehouse
- Enforcing tagging standards externally
- Managing access rights for vendor staff
- Tracking version updates in external models
- Conducting periodic vendor data reviews
Module 12. Future-Proofing Data Models for Revisions
Build adaptability into data systems so updates to Basel rules don’t require full reengineering.
12 chapters in this module
- Monitoring BCBS for upcoming changes
- Building modular data transformation layers
- Creating configurable thresholds for risk weights
- Versioning logic by regulation cycle
- Isolating rule-specific components
- Creating sandbox environments for testing
- Planning for IFRS 17 interoperability
- Integrating with regulatory change tracking tools
- Documenting change impact assessments
- Alerting teams on proposed rule changes
- Scheduling periodic model revalidations
- Archiving deprecated data logic securely
How this maps to your situation
- Regulatory capital data design
- Risk-weighted asset pipelines
- Leverage ratio implementation
- Internal model governance
Before vs. after
Before
Manual, siloed data processes that require constant rework and leave gaps in audit readiness
After
Structured, traceable, and future-proof data pipelines that directly support Basel III compliance and capital reporting
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 90 minutes per week over 12 weeks, designed to fit around core responsibilities.
If nothing changes
Continuing with fragmented data logic increases exposure to regulatory scrutiny, model rejection, and costly remediation cycles during audits or leadership transitions.
How this compares to the alternatives
Unlike generic regulatory training, this course focuses specifically on the data engineering layer beneath Basel III , giving practitioners like you direct ownership over the logic that feeds capital decisions.
Frequently asked
Who is this course designed for?
Senior BI developers and data engineers in financial institutions who contribute to regulatory capital reporting under Basel III.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this cover Basel IV or future revisions?
The course focuses on current Basel III implementation, with a dedicated module on future-proofing for upcoming changes.
$199 one-time. Approximately 90 minutes per week over 12 weeks, designed to fit around core responsibilities..
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