This professional course introduces participants to the tools and methodologies used to build, interpret, and apply credit risk models and internal credit rating frameworks. Designed for credit risk analysts, quants, and financial modelers, the training course blends statistical techniques with regulatory expectations. Participants will understand how to model probability of default (PD), loss given default (LGD), and exposure at default (EAD), and how to implement scoring and rating systems for sound credit decision-making.
Excel-based modeling and scoring exercises
Case studies on rating model development and validation
Interactive demonstrations of PD, LGD, EAD calculations
Framework alignment with Basel and IFRS 9 standards
Understand the components of credit risk modeling (PD, LGD, EAD)
Develop and calibrate internal credit rating and scoring models
Apply logistic regression and decision tree techniques
Align models with regulatory and audit requirements
Validate and back-test risk models effectively
Use risk models for capital allocation and provisioning decisions
Interpret and communicate model outputs to stakeholders
Session 1: Introduction to Credit Risk Modeling
Risk components: PD, LGD, EAD, and Expected Loss (EL)
Use cases in credit assessment, pricing, capital, provisioning
Overview of rating models vs scoring models
Session 2: Probability of Default (PD) Modeling
Definition and data needed for PD
Logistic regression for binary outcomes
Model discrimination (ROC, Gini) and calibration
Session 3: Internal Rating Systems and Scorecards
Mapping qualitative and quantitative factors
Designing scorecards for different borrower types
Tiered rating assignment and overrides
Session 1: LGD and EAD Estimation Techniques
Historical LGD and downturn LGD
Collateral valuation and recovery assumptions
EAD assumptions for drawn and undrawn exposures
Session 2: Model Validation and Monitoring
Back-testing, benchmarking, and override tracking
Model risk management and documentation standards
Independent validation roles and governance
Session 3: Aligning with IFRS 9 and Basel Requirements
Lifetime vs 12-month PD
Staging under IFRS 9 (Stage 1–3) and provisioning impact
IRB model usage under Basel II/III/IV
Session 1: Using Credit Models in Lending and Strategy
Model-informed decision-making (acceptance, limits, pricing)
Integration with loan origination and monitoring platforms
Credit rating triggers and covenant planning
Session 2: Communicating Credit Model Insights
Dashboards and executive reporting formats
Visualizing model outputs for committees and boards
Key Risk Indicators (KRIs) based on modeled insights
Session 3: Group Simulation – Model Design and Application
Participants simulate a rating model for SME/corporate borrowers
Discuss design logic, risk parameters, and governance needs
Final presentations and feedback
We are open to customizing this program to align with your specific learning objectives. If your team has particular goals or areas they wish to focus on, we would be happy to tailor the course outline to meet those needs and ensure the program supports the achievement of your desired outcomes.
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