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Credit risk modeling

Enhancing credit risk modeling: tools and techniques

28 April 2019 - 29 April 2019, 8:30AM - 4:00PM, GST Dubai, United Arab Emirates


Course overview

Following the renewed emphasis expressed by central banks and regulators, banks around the world have gradually begun investing in data systems and analytics to strengthen their risk management practices. This two-day course has been designed to help participants shift their focus from basic reporting and exploratory analysis towards designing credit risk models generating powerful insights and having stronger business impacts.

Who should attend

This course is highly recommended for credit risk management professionals, accountants, auditors, bankers, financial advisors, credit analysts, treasury managers, risk analysts and scholars who are involved in management, development, or validation of credit risk models.


Participants who attend all sessions will be awarded a KPMG certificate of attendance.


To register online, please click here.







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Day one Day two

Overview and regulatory requirements
—Introduction to credit risk modeling
—Overview of the regulatory environment
—Introduction to credit risk
—Definition and types
—Default definition
—Expected loss vs unexpected loss
—Internal and external ratings
—Macro-economic variables and key industry risks
—Basel accords
—IFRS 9 – Impairment
—Modeling framework
—Elements of credit risk modeling

Probability of default and loss given default models
—Introduction to probability of default
—Data requirements
—Logistic regression
—Variable selection
—Model output
—Industry benchmarks for PD estimates
—Assignment/case study
—Introduction to loss given default
—Data requirements
—Workout method
—Model output
—Industry benchmarks for LGD estimates
—Assignment/case study
—Using PD & LGD estimates for business decision purposes









Exposure at default models
—Introduction to exposure at default
—Use of Credit Conversion Factor (CCF)
—CCF calculation methods – Fixed horizon
—Model output

Macroeconomic modeling and stress testing
—Introduction to macroeconomic modeling and stress testing
—Regulatory requirements —
Potential variables considered
—Scenario modeling
—Linear regression
—Model fit indicators
—Assumption testing
—Serial correlation
—Model output

Model validation and benchmarking
—Model validation components
—Roles and responsibilities
—Qualitative validation
—Quantitative validation
—Discriminatory power
—Model monitoring
—Results and reporting