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FIN3782 Mastering Basel III for Data Scientists in Financial Services

$199.00
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A tailored course, built for your situation

Mastering Basel III for Data Scientists in Financial Services

Build authority in regulatory capital frameworks without leaving the data stack.

$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.
You built the model. Now explain how it satisfies Basel III’s output floor, under audit conditions.

The situation this course is for

Data Scientists are increasingly on the hook for justifying how models feed into capital calculations, yet most weren’t trained in the structure of Basel III’s risk-weighted asset logic or the difference between standardized and internal approaches. When the audit team asks for traceability from code to capital ratio, hesitation creeps in, not because the work isn’t sound, but because the framework isn’t fluent.

Who this is for

Mid-career Data Scientists in banking and asset management who own risk, valuation, or stress-testing models and are being pulled into regulatory conversations they weren’t trained for.

Who this is not for

This is not for compliance officers building control documentation, nor for executives interpreting capital ratios at a strategic level. It’s for technical practitioners who need to close the gap between code and capital adequacy.

What you walk away with

  • Map any risk model output directly to Basel III capital requirements with zero hand-offs
  • Speak confidently during audit interviews using exact framework language
  • Anticipate data traceability requests before they land in your inbox
  • Embed regulatory logic into model documentation so reviewers move faster
  • Differentiate your contributions in cross-functional risk meetings

The 12 modules (with all 144 chapters)

Module 1. Basel III Architecture Overview
Understand the three pillars, their evolution, and how U.S. implementation differs under Fed and OCC rules.
12 chapters in this module
  1. Core objectives behind the Basel III framework post-the current cycle
  2. How the U.S. market adoption timeline differs from global peers
  3. Structure of the Basel Committee on Banking Supervision
  4. Pillar 1: Minimum capital requirements explained
  5. Pillar 2: Supervisory review process in practice
  6. Pillar 3: Market discipline and disclosure mandates
  7. Key differences between Basel II and Basel III frameworks
  8. The role of national regulators in local enforcement
  9. How Basel III interacts with Dodd-Frank Act provisions
  10. Timeline of major revisions including the endgame proposals
  11. Impact of Basel III on U.S. GSIBs and intermediate holding companies
  12. Where data scientists first encounter Basel III in workflows
Module 2. Risk-Weighted Assets and Your Models
Break down how credit, market, and operational risk models feed into RWA calculations.
12 chapters in this module
  1. Defining risk-weighted assets for capital adequacy purposes
  2. How exposure at default is derived from model outputs
  3. Understanding loss given default in internal ratings-based models
  4. Probability of default modeling under Basel constraints
  5. Treating counterparty credit risk in derivatives portfolios
  6. Standardized Approach vs Internal Ratings-Based approach
  7. Foundation vs Advanced IRB: implications for data inputs
  8. How your classification models impact risk buckets
  9. Treatment of off-balance sheet exposures
  10. Large exposures framework and concentration risk
  11. Operational risk AMA to SA-CCR transition
  12. Data granularity expectations for risk-weight assignment
Module 3. Capital Adequacy and Leverage Ratios
Trace how models support Tier 1, Tier 2, and leverage ratio calculations.
12 chapters in this module
  1. Components of Common Equity Tier 1 capital
  2. Additional Tier 1 capital instruments and their treatment
  3. Tier 2 capital and subordinated debt rules
  4. How model outputs affect capital deductions
  5. CET1 ratio calculation from balance sheet and risk weights
  6. Total capital ratio and regulatory minimums
  7. Leverage ratio formula and its independence from risk models
  8. Supplementary Leverage Ratio in U.S. regulatory context
  9. Impact of clearing and repo activities on leverage exposure
  10. Understanding the output floor and its impact on model scaling
  11. Basel III endgame changes to capital ratios proposed right now
  12. Interactions between SLR and risk-based capital requirements
Module 4. Data Traceability for Regulatory Review
Design model documentation that survives auditor scrutiny and supports internal capital reporting.
12 chapters in this module
  1. Expected documentation depth for model risk managers
  2. Linking model inputs to Basel-defined exposure categories
  3. Versioning data pipelines for audit readiness
  4. Proving independence of validation datasets
  5. How to structure model assumptions for regulatory review
  6. Mapping feature engineering to risk classification logic
  7. Documenting treatment of outliers and missing data
  8. Maintaining lineage from code to capital output
  9. Best practices for documenting fallback methodologies
  10. Review cycle expectations from internal and external auditors
  11. Preparing for on-site examiner requests
  12. Common feedback loops from FR Y-14A submissions
Module 5. Stress Testing and CCAR Integration
Align predictive models with CCAR and DFAST scenarios and reporting logic.
12 chapters in this module
  1. Overview of CCAR and DFAST requirements
  2. How macroeconomic scenarios map to model inputs
  3. Designing forward-looking loss estimates for capital planning
  4. Incorporating unemployment and GDP shocks into models
  5. Time horizons for baseline, adverse, and severely adverse scenarios
  6. Loss rate modeling under stressed conditions
  7. Portfolio segmentation for scenario application
  8. Model validation expectations during CCAR
  9. Treatment of qualitative adjustments in submissions
  10. Documentation required for Fed review teams
  11. Handling multi-year projections in capital forecasts
  12. Coordination points with finance and risk teams
Module 6. Internal Capital Adequacy Assessment Process
Understand how firm-level ICAAP uses data models to justify internal capital floors.
12 chapters in this module
  1. Purpose and structure of ICAAP documentation
  2. Role of stress testing results in capital buffers
  3. Incorporating model risk into capital add-ons
  4. How business unit risk profiles inform capital allocation
  5. Scenario design beyond regulatory minimums
  6. Reverse stress testing expectations
  7. Governance of ICAAP by senior management
  8. Documentation flow from model to board summary
  9. Frequency and trigger events for ICAAP updates
  10. Internal audit expectations on ICAAP processes
  11. Linking ICAAP to dividend and buyback planning
  12. How model uncertainty is reflected in internal buffers
Module 7. Model Risk Management Expectations
Meet SR 11-7 requirements for validation, governance, and oversight.
12 chapters in this module
  1. Key principles of SR 11-7 supervisory guidance
  2. Model lifecycle governance from development to retirement
  3. Validation expectations for quantitative analysts
  4. Segregation of duties in model development teams
  5. Documentation standards for challenger models
  6. Frequency of model performance monitoring
  7. Thresholds for model recalibration or replacement
  8. Using backtesting to prove model stability
  9. Requirements for model inventory and metadata
  10. Audit trail expectations for code and data changes
  11. Handling data drift in regulatory models
  12. Third-party model review readiness
Module 8. Advanced Analytics in Basel Compliance
Apply machine learning techniques while staying within regulatory boundaries.
12 chapters in this module
  1. Permissible use cases for ML in capital models
  2. Avoiding black-box pitfalls in credit risk scoring
  3. Model interpretability requirements under SR 11-7
  4. Feature importance analysis for regulatory reporting
  5. Using ensembles without sacrificing transparency
  6. Stability testing for ML-driven risk outputs
  7. Validating non-linear models in stress scenarios
  8. Benchmarking ML models against traditional approaches
  9. Handling concept drift in long-running models
  10. Documentation requirements for hyperparameter tuning
  11. Explainability tools accepted by examiners
  12. When to fall back to simpler models for clarity
Module 9. Liquidity Coverage Ratio and Data Models
Support LCR and NSFR calculations with accurate cash flow modeling.
12 chapters in this module
  1. Structure of the Liquidity Coverage Ratio
  2. Stock vs flow modeling in LCR calculations
  3. Categorizing HQLA assets in data systems
  4. Runoff rate assumptions for deposits and lines
  5. Behavioral assumptions in retail and wholesale funding
  6. Time bucketing for cash inflows and outflows
  7. Interagency LCR reporting requirements
  8. Modeling stressed net cash outflows
  9. Net Stable Funding Ratio calculation basics
  10. Available stable funding classifications
  11. Required stable funding by asset type
  12. Data challenges in long-term liquidity forecasting
Module 10. Cross-Jurisdictional Regulatory Alignment
Navigate differences between U.S. Basel III implementation and global peers.
12 chapters in this module
  1. Fed’s version of Basel III endgame vs BCBS standards
  2. Treatment of municipal bonds in U.S. capital rules
  3. Community bank exemptions and thresholds
  4. Differences between U.S. SLR and European ratios
  5. OCC vs Fed expectations on capital planning
  6. Handling foreign subsidiary risk exposure
  7. Consolidated vs standalone reporting scopes
  8. Impact of foreign regulatory requirements on U.S. banks
  9. IOSCO principles for risk data aggregation
  10. BCBS 239 compliance expectations for data systems
  11. Cross-border data sharing under Basel oversight
  12. Time zone and latency considerations in global reporting
Module 11. Vendor Model Oversight and Integration
Ensure third-party models comply with internal and regulatory standards.
12 chapters in this module
  1. Due diligence for purchased risk models
  2. Mapping vendor documentation to Basel requirements
  3. Validation expectations for outsourced models
  4. Contractual clauses that support audit rights
  5. Service level agreements for model updates
  6. Handling model drift in vendor-provided scores
  7. Integrating external data feeds into internal frameworks
  8. Documentation standards for API-driven models
  9. Governance of cloud-hosted risk platforms
  10. Cyber risk considerations in vendor model use
  11. Exit strategies for third-party models
  12. Maintaining internal expertise despite vendor reliance
Module 12. Future-Proofing Your Regulatory Fluency
Stay ahead of proposed changes and firm-specific implementation timelines.
12 chapters in this module
  1. Tracking Basel Committee consultation papers
  2. Engaging with internal policy teams on feedback
  3. Understanding U.S. proposal timelines for endgame rules
  4. Preparing for output floor implementation right now
  5. Anticipating changes to operational risk capital
  6. Monitoring developments in climate risk capital charges
  7. Engaging with Fed examiners proactively
  8. Building a personal curriculum for regulatory evolution
  9. Contributing to cross-functional working groups
  10. Positioning yourself as a bridge between data and compliance
  11. Creating reusable templates for future audits
  12. Developing a personal brand in regulatory data science

How this maps to your situation

  • When the audit team asks for traceability from model output to capital ratio
  • Before the next CCAR submission cycle begins
  • When onboarding a third-party model used in risk calculations
  • After receiving feedback from model validation on documentation depth

Before vs. after

Before
Models are built to spec, but connecting them to capital adequacy feels like a separate silo.
After
You can walk an auditor through the full chain from code to CET1 without breaking stride.

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 three months, with self-paced access.

If nothing changes
Without framework fluency, even accurate models risk being sidelined in capital discussions , or worse, rewritten by teams less familiar with the data.

How this compares to the alternatives

Generic compliance courses teach high-level principles. This course gives you exact mappings between model features and Basel-defined risk buckets , so you know not just what to document, but why it matters.

Frequently asked

Do I need a finance or regulatory background to benefit from this?
No. The course is designed for data professionals who understand modeling but need clarity on how their work fits into Basel III’s capital framework.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me with audit preparation?
Yes. Each module includes templates and examples tailored to common auditor questions about model traceability and risk classification.
$199 one-time. Approximately 90 minutes per week over three months, with self-paced access..

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
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