Credit Risk Modelling Certification Training

This Credit Risk Modelling certification training is a comprehensive 20-hour online BFSI program designed to equip professionals with in-depth knowledge and practical skills for building, evaluating and applying credit risk models used by banks, financial institutions and risk management teams. This course covers the fundamentals of credit risk measurement and modelling, including key risk parameters (PD, LGD, EAD), regulatory and supervisory expectations, modern modelling challenges and forward-looking elements such as IFRS 9 Expected Credit Loss (ECL).

Participants will learn how credit models support provisioning, capital frameworks (including ICAAP and Basel III/IV), and governance requirements, and they will get practical exposure to risk staging, data considerations, validation techniques and model governance. By the end of the training, learners will be prepared to contribute effectively to credit risk modelling and risk management decisions in real-world contexts.

Module 1 - Challenges in Estimating Credit Losses

• Introduction: reserving for loan losses
  • Purpose of loan-loss reserves in the risk management framework
  • Interaction with lending, pricing, capital, and provisioning


• Track record and evolution of credit-risk models
  • Historical modelling limitations and lessons learned
  • Risk concept foundations: expected loss (EL) and unexpected loss (UL)


• Buffers against loss: reserves vs. capital
  • Accounting reserves vs. economic capital
  • How models feed into both


• Economic and regulatory capital
  • ICAAP, Basel III/IV considerations
  • Relationship between capital, provisioning, and risk appetite


• Modern modelling challenges (2025)
  • Model instability, regime shifts, macro dependencies, data quality
  • Introduction to modelling uncertainty and overlays (high-level)



Module 2 - Recent Regulatory and Supervisory Initiatives

• Basel regulatory environment (2025)
  • IRB / AIRB guidelines
  • Revised definition of default
  • Basel III/IV expectations for PD/LGD/EAD models


• European regulatory guidance
  • ECB guidance on nonperforming loans (NPLs)
  • Supervisory reviews and TRIM-style expectations


• Tightened definition of default
  • 90 days past due, unlikeliness to pay, forbearance rules
  • Impact on modelling, staging, and rating systems
  • Data segmentation and governance implications


• Global regulatory themes relevant in 2025
  • Model Risk Management (MRM) expectations
  • Validation and back-testing standards
  • Increased scrutiny on forward-looking components



Module 3 - Estimation of Key Credit Risk Parameters: Best Practices

• Probability of Default (PD)
  • Rating systems, scoring models, calibration
  • Long-run vs. point-in-time PDs
  • Low-default portfolios and advanced estimation approaches


• Loss Given Default (LGD)
  • Workout models, recovery data, collateral valuation
  • Downturn LGD and regulatory requirements
  • Secured vs. unsecured, cure rates, write-offs


• Exposure at Default (EAD)
  • Credit conversion factors (CCFs)
  • Limit utilisation modelling
  • Behavioural and product-specific considerations


• Validation and Governance
  • Back-testing, benchmarking, discriminatory power tests
  • Model monitoring and performance thresholds
  • Documentation standards
  • Supervisory expectations (SR 11-7-aligned)


• Modern Modelling Trends
  • Hybrid statistical + machine learning models (high-level)
  • Model explainability & regulatory acceptance



Module 4 - IFRS 9 Requirements and Core Definitions

• IFRS 9 overview and conceptual foundation
  • Expected Credit Loss (ECL) framework
  • Reasonable & supportable forecasts
  • Definition of default under IFRS 9


• Three-stage approach
  • Stage 1 (12-month ECL)
  • Stage 2 (lifetime ECL)
  • Stage 3 (credit-impaired assets)


• Case examples
  • Transition from Stage 1 → Stage 2
  • Credit deterioration examples
  • Impact of collateral and restructuring


• Key differences between IFRS 9 & other risk measures
  • CECL vs IFRS 9 (conceptual differences)
  • Divergence between regulatory PD/LGD/EAD and accounting parameters
  • Divergence between risk management vs financial reporting objectives



Module 5 - IFRS 9 Staging, ECL Modelling & Forward-Looking Elements

• Criteria for Significant Increase in Credit Risk (SICR)
  • Quantitative and qualitative measures
  • Rebuttable presumption rules & risk-based thresholds


• Lifetime loss estimation
  • Methods for projecting lifetime PD/EAD/LGD
  • Transition matrix approaches
  • Survival and hazard models


• Forward-looking scenarios
  • Designing baseline, adverse, and severe
  • Scenario weights and macroeconomic drivers
  • Modelling non-linearity and regime changes


• Judgment & governance
  • Use of overlays and qualitative adjustments
  • Avoiding double counting
  • Documentation and audit expectations


• Hands-on walkthrough
  • Mini ECL calculation using sample data

• Basic understanding of banking or finance
• Familiarity with credit concepts like loans and risk (PD, LGD, EAD)
• Comfort with simple quantitative concepts (basic statistics)
• No prior deep regulatory or modelling experience required

• Banking and finance professionals seeking credit risk knowledge
• Credit analysts, officers, and portfolio managers
• Risk management and compliance staff with limited prior exposure
• Finance or accounting professionals involved in loan monitoring
• Anyone interested in understanding IFRS 9 and credit risk modelling basics

• On successful completion of the course and assessment, you will receive a Course Completion Certificate from Merit Global.

Earning the Credit Risk Modelling Certification can be a powerful differentiator for professionals aiming to deepen their expertise and accelerate their careers in financial risk management. This specialized training equips you with practical skills and knowledge to build, evaluate and apply credit risk models - including key risk parameters like Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD), as well as regulatory frameworks such as Basel III/IV and IFRS 9 Expected Credit Loss (ECL). These competencies are essential for roles within banks, credit risk teams and financial institutions where quantifying and managing credit risk is critical to sound decision-making and regulatory compliance. By showing employers your ability to translate complex modelling concepts into actionable risk insights, the certification enhances your credibility and readiness for higher-impact positions.

From a compensation perspective, professionals with solid credit risk and modelling skills are well positioned to benefit financially as demand grows for risk-savvy talent. In markets like Dubai and the UAE, senior quantitative roles such as credit risk modelers can command around $80,000–$110,000 USD per year (approximately AED 295,000–AED 405,000) or more depending on experience and firm size, reflecting the value placed on technical expertise. Globally, credit risk analysts and related risk professionals often see higher salary trajectories as they move into mid- and senior-level roles; certifications and specialized training can accelerate that progression by signalling commitment to rigour and ongoing professional development. In addition to stronger earning potential, certified practitioners often find broader opportunities in risk analytics, regulatory reporting, stress testing and capital planning

He is a seasoned credit risk specialist with extensive experience in building and validating risk models for financial institutions and corporate credit portfolios. With deep expertise in statistical modelling, PD/LGD/EAD frameworks and regulatory expectations, he brings practical insights into designing robust, data‑driven credit risk solutions. Known for his clear and engaging training style, he breaks down complex quantitative concepts into actionable learning that professionals can apply immediately. His guidance equips learners with the skills and confidence to develop, evaluate and implement effective credit risk models.

Learning Outcomes:

• Explain the key challenges and evolution of credit risk modelling and its role in risk management frameworks.
• Differentiate between expected loss (EL) and unexpected loss (UL) and understand their implications for capital and provisioning.
• Interpret and apply regulatory requirements related to credit risk models under Basel III/IV and supervisory expectations.
• Estimate core credit risk parameters, including Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD) using best-practice techniques.
• Apply model validation principles, including back-testing, benchmarking and governance standards consistent with regulatory expectations.
• Understand and implement the IFRS 9 Expected Credit Loss (ECL) framework, including staging, forward-looking elements and scenario design.
• Incorporate forward-looking macroeconomic scenarios into credit risk estimation and staging decisions.
• Demonstrate practical modelling concepts through hands-on examples and case discussions to support decision-making in credit risk and capital planning.