Banking & Financial Services
IFRS 9 Expected Credit Losses Building Models for Central Banks
A five-day programme on building IFRS 9 expected credit loss models for central bank portfolios, covering staging, PD, LGD and EAD estimation, scenario weighting, ECL computation, validation, and model governance.
Introduction
The IFRS 9 Expected Credit Losses Building Models for Central Banks Training Course prepares risk, finance, and modelling professionals to build expected credit loss models for central bank portfolios. IFRS 9 requires forward-looking impairment rather than waiting for losses to appear. That requirement demands data, statistical models, macroeconomic scenarios, and governance that stand up to audit scrutiny. This course works through the model build step by step. It covers staging logic, PD, LGD and EAD estimation, scenario weighting, and validation. Furthermore, it applies model governance and documentation standards. As a result, participants can construct defensible ECL models and explain the numbers.
IFRS 9 Expected Credit Losses Building Models for Central Banks Course Objectives
- Explain the IFRS 9 impairment model and its three-stage structure.
- Apply staging criteria and significant increase in credit risk rules.
- Build probability of default models for sovereign, interbank, and corporate exposures.
- Estimate loss given default using collateral, recovery, and workout data.
- Calculate exposure at default including commitments and utilisation patterns.
- Design macroeconomic scenarios and probability weightings.
- Compute expected credit loss and reconcile results to the financial statements.
- Apply model validation, backtesting, and discriminatory power metrics.
- Document methodology, assumptions, and model governance requirements.
- Assess model risk, sensitivity, and disclosure requirements.
Course Methodology
- Interactive lectures with central bank portfolio and disclosure examples.
- Data preparation and model build workshops using sample datasets.
- Scenario design and probability weighting exercises.
- Validation, backtesting, and sensitivity analysis practice.
- Structured peer discussion with facilitator feedback on model design choices.
Who Should Take This Course
- Credit risk modelling and quantitative analysts.
- Finance and reporting professionals covering provisions.
- Risk managers in banks and central banks.
- Internal auditors reviewing model governance.
- Supervisors assessing provisioning practices.
- Treasury and portfolio analysts managing held securities.
IFRS 9 Expected Credit Losses Building Models for Central Banks Course Outlines
IFRS 9 Impairment Framework
- • The impairment objective and the expected credit loss concept.
- • Three-stage model: performing, underperforming, and credit-impaired.
- • Significant increase in credit risk: quantitative and qualitative triggers.
- • Low credit risk exemption and 12-month versus lifetime ECL.
- • Default definitions and their effect on staging.
- • Interaction with classification and measurement categories.
- • Case study: staging decisions in a central bank securities portfolio.
Probability of Default Modelling
- • PD concepts: point-in-time versus through-the-cycle.
- • Data requirements: default history, ratings, and exposure records.
- • Statistical techniques: logistic regression and survival analysis.
- • Rating scale design and calibration approaches.
- • Incorporating forward-looking information into PD.
- • Low-default portfolios and expert judgement adjustments.
- • Workshop: building a PD model for a sovereign and corporate portfolio.
Loss Given Default and Exposure at Default
- • LGD components: exposure, collateral, and recovery costs.
- • Recovery rates, cure rates, and workout timelines.
- • Collateral valuation, haircuts, and guarantee treatment.
- • EAD estimation and credit conversion factors for commitments.
- • Utilisation patterns and prepayment behaviour.
- • Treatment of off-balance-sheet and contingent exposures.
- • Workshop: estimating LGD and EAD from recovery data.
Scenario Design and ECL Calculation
- • Macroeconomic variables relevant to credit risk.
- • Scenario construction, severity calibration, and probability weighting.
- • Multiple scenario approaches and weighted average ECL.
- • Discounting, effective interest rate, and cash flow timing.
- • Aggregation across portfolios and reconciliation to accounts.
- • Disclosure requirements and movement schedules.
- • Workshop: computing weighted ECL across three scenarios.
Validation, Governance, and Model Risk
- • Model validation framework and independent review.
- • Backtesting, benchmarking, and discriminatory metrics.
- • Sensitivity analysis and stress testing of model outputs.
- • Model documentation and assumption registers.
- • Governance, approval, and periodic model review cycles.
- • Model risk management and audit readiness.
- • Course review, assessment, and action planning.
Conclusion
By successfully completing IFRS 9 Expected Credit Losses Building Models for Central Banks, participants will gain a thorough understanding of staging logic, PD, LGD and EAD estimation, scenario weighting, validation, and model governance. They will also acquire practical skills in data preparation, model construction, ECL computation, and documentation. In addition, the course prepares them to build defensible models that satisfy auditors and supervisors. Gentex Training Center delivers this programme with a strong focus on applied modelling practice and measurable reporting accuracy.
FAQs for IFRS 9 Expected Credit Losses Building Models for Central Banks course
— What is the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course about?
It is a five-day programme on building expected credit loss models under IFRS 9 for central bank portfolios. It covers staging criteria, PD, LGD and EAD estimation, macroeconomic scenario weighting, ECL computation, model validation, and governance documentation.
— What are the key benefits of the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course?
Participants gain the practical ability to build models rather than only interpret them, which reduces provisioning surprises. The course improves staging accuracy, strengthens data and assumption quality, sharpens validation and benchmarking, prepares models for audit and supervisory review, and gives finance teams credible numbers to explain in disclosures.
— What skills will I gain from the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course?
Participants gain IFRS 9 staging and significant increase in credit risk assessment, probability of default, loss given default and exposure at default model building, macroeconomic scenario design and expected credit loss computation, and model validation, documentation and governance assessment. These four skills cover the complete ECL modelling cycle.
— What tools, methods, or standards are covered in the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course?
The course covers the three-stage impairment model, significant increase in credit risk triggers, the low credit risk exemption, 12-month and lifetime expected credit loss, probability of default and loss given default estimation, credit conversion factors for exposure at default, collateral haircuts and guarantee treatment, logistic regression and survival analysis, point-in-time and through-the-cycle calibration, macroeconomic scenario construction and probability weighting, effective interest rate discounting, weighted average ECL, movement and disclosure schedules, backtesting and benchmarking metrics, sensitivity analysis, and model documentation and governance standards.
— How is the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course applied in real-world practice?
Participants apply the methods to their own portfolios. They prepare exposure and default data, build and calibrate PD, LGD and EAD models, design scenarios with probability weights, compute expected credit loss, prepare disclosure movements, and document assumptions for audit. Many leave with a working model structure and validation plan for their institution.
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Introduction
The IFRS 9 Expected Credit Losses Building Models for Central Banks Training Course prepares risk, finance, and modelling professionals to build expected credit loss models for central bank portfolios. IFRS 9 requires forward-looking impairment rather than waiting for losses to appear. That requirement demands data, statistical models, macroeconomic scenarios, and governance that stand up to audit scrutiny. This course works through the model build step by step. It covers staging logic, PD, LGD and EAD estimation, scenario weighting, and validation. Furthermore, it applies model governance and documentation standards. As a result, participants can construct defensible ECL models and explain the numbers.
IFRS 9 Expected Credit Losses Building Models for Central Banks Course Objectives
- Explain the IFRS 9 impairment model and its three-stage structure.
- Apply staging criteria and significant increase in credit risk rules.
- Build probability of default models for sovereign, interbank, and corporate exposures.
- Estimate loss given default using collateral, recovery, and workout data.
- Calculate exposure at default including commitments and utilisation patterns.
- Design macroeconomic scenarios and probability weightings.
- Compute expected credit loss and reconcile results to the financial statements.
- Apply model validation, backtesting, and discriminatory power metrics.
- Document methodology, assumptions, and model governance requirements.
- Assess model risk, sensitivity, and disclosure requirements.
Course Methodology
- Interactive lectures with central bank portfolio and disclosure examples.
- Data preparation and model build workshops using sample datasets.
- Scenario design and probability weighting exercises.
- Validation, backtesting, and sensitivity analysis practice.
- Structured peer discussion with facilitator feedback on model design choices.
Who Should Take This Course
- Credit risk modelling and quantitative analysts.
- Finance and reporting professionals covering provisions.
- Risk managers in banks and central banks.
- Internal auditors reviewing model governance.
- Supervisors assessing provisioning practices.
- Treasury and portfolio analysts managing held securities.
IFRS 9 Expected Credit Losses Building Models for Central Banks Course Outlines
IFRS 9 Impairment Framework
- • The impairment objective and the expected credit loss concept.
- • Three-stage model: performing, underperforming, and credit-impaired.
- • Significant increase in credit risk: quantitative and qualitative triggers.
- • Low credit risk exemption and 12-month versus lifetime ECL.
- • Default definitions and their effect on staging.
- • Interaction with classification and measurement categories.
- • Case study: staging decisions in a central bank securities portfolio.
Probability of Default Modelling
- • PD concepts: point-in-time versus through-the-cycle.
- • Data requirements: default history, ratings, and exposure records.
- • Statistical techniques: logistic regression and survival analysis.
- • Rating scale design and calibration approaches.
- • Incorporating forward-looking information into PD.
- • Low-default portfolios and expert judgement adjustments.
- • Workshop: building a PD model for a sovereign and corporate portfolio.
Loss Given Default and Exposure at Default
- • LGD components: exposure, collateral, and recovery costs.
- • Recovery rates, cure rates, and workout timelines.
- • Collateral valuation, haircuts, and guarantee treatment.
- • EAD estimation and credit conversion factors for commitments.
- • Utilisation patterns and prepayment behaviour.
- • Treatment of off-balance-sheet and contingent exposures.
- • Workshop: estimating LGD and EAD from recovery data.
Scenario Design and ECL Calculation
- • Macroeconomic variables relevant to credit risk.
- • Scenario construction, severity calibration, and probability weighting.
- • Multiple scenario approaches and weighted average ECL.
- • Discounting, effective interest rate, and cash flow timing.
- • Aggregation across portfolios and reconciliation to accounts.
- • Disclosure requirements and movement schedules.
- • Workshop: computing weighted ECL across three scenarios.
Validation, Governance, and Model Risk
- • Model validation framework and independent review.
- • Backtesting, benchmarking, and discriminatory metrics.
- • Sensitivity analysis and stress testing of model outputs.
- • Model documentation and assumption registers.
- • Governance, approval, and periodic model review cycles.
- • Model risk management and audit readiness.
- • Course review, assessment, and action planning.
Conclusion
By successfully completing IFRS 9 Expected Credit Losses Building Models for Central Banks, participants will gain a thorough understanding of staging logic, PD, LGD and EAD estimation, scenario weighting, validation, and model governance. They will also acquire practical skills in data preparation, model construction, ECL computation, and documentation. In addition, the course prepares them to build defensible models that satisfy auditors and supervisors. Gentex Training Center delivers this programme with a strong focus on applied modelling practice and measurable reporting accuracy.
FAQs for IFRS 9 Expected Credit Losses Building Models for Central Banks course
— What is the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course about?
It is a five-day programme on building expected credit loss models under IFRS 9 for central bank portfolios. It covers staging criteria, PD, LGD and EAD estimation, macroeconomic scenario weighting, ECL computation, model validation, and governance documentation.
— What are the key benefits of the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course?
Participants gain the practical ability to build models rather than only interpret them, which reduces provisioning surprises. The course improves staging accuracy, strengthens data and assumption quality, sharpens validation and benchmarking, prepares models for audit and supervisory review, and gives finance teams credible numbers to explain in disclosures.
— What skills will I gain from the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course?
Participants gain IFRS 9 staging and significant increase in credit risk assessment, probability of default, loss given default and exposure at default model building, macroeconomic scenario design and expected credit loss computation, and model validation, documentation and governance assessment. These four skills cover the complete ECL modelling cycle.
— What tools, methods, or standards are covered in the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course?
The course covers the three-stage impairment model, significant increase in credit risk triggers, the low credit risk exemption, 12-month and lifetime expected credit loss, probability of default and loss given default estimation, credit conversion factors for exposure at default, collateral haircuts and guarantee treatment, logistic regression and survival analysis, point-in-time and through-the-cycle calibration, macroeconomic scenario construction and probability weighting, effective interest rate discounting, weighted average ECL, movement and disclosure schedules, backtesting and benchmarking metrics, sensitivity analysis, and model documentation and governance standards.
— How is the "IFRS 9 Expected Credit Losses Building Models for Central Banks" course applied in real-world practice?
Participants apply the methods to their own portfolios. They prepare exposure and default data, build and calibrate PD, LGD and EAD models, design scenarios with probability weights, compute expected credit loss, prepare disclosure movements, and document assumptions for audit. Many leave with a working model structure and validation plan for their institution.
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