Credit Risk Measurement and Loss Given Default (LGD) Training

About This Course

Credit risk remains the single largest source of financial loss for banks, development finance institutions, and corporate lenders worldwide. The accurate measurement of credit risk — and in particular the estimation of Loss Given Default (LGD) — sits at the heart of sound lending decisions, regulatory capital adequacy, and portfolio management strategy. As Basel III and IFRS 9 requirements continue to reshape risk frameworks across emerging and developed markets, demand for practitioners who can build, validate, and interpret LGD models has never been greater.

This five-day training programme offered by TrainingComplex provides a comprehensive, practitioner-oriented grounding in credit risk measurement, with a deep focus on LGD estimation methodologies. Participants will move from foundational concepts — the credit risk triangle of probability of default (PD), loss given default (LGD), and exposure at default (EAD) — through to advanced model-building techniques, regulatory capital calculations under the Internal Ratings-Based (IRB) approach, and the treatment of collateral and recovery processes in LGD quantification.

The course is structured to balance conceptual rigour with practical application. Each module incorporates real-world data scenarios, worked calculation exercises, and case studies drawn from retail banking, corporate lending, and microfinance portfolios. Participants will leave equipped not only to understand LGD in theory, but to design, test, and challenge LGD models within their own institutions — satisfying both internal risk governance expectations and external regulatory scrutiny.

TrainingComplex's expert facilitators bring direct experience from banking supervision, credit portfolio management, and model validation, ensuring that every concept is anchored in current market practice and regulatory expectation.

Who Should Attend

• Credit risk analysts and senior credit officers in commercial and development banks
• Risk model developers and model validation specialists
• Financial controllers and CFOs responsible for IFRS 9 provisioning
• Bank examiners, prudential supervisors, and central bank staff
• Internal auditors reviewing credit risk frameworks and capital models
• Portfolio managers and treasury professionals managing credit-sensitive instruments
• Consultants and advisors supporting financial institutions on Basel compliance
• Microfinance institution (MFI) risk managers adapting LGD concepts to their portfolios

Learning Objectives

• Define the components of expected credit loss — PD, LGD, and EAD — and explain how each contributes to regulatory capital and provisioning calculations
• Distinguish between workout LGD, market LGD, and implied market LGD and select the appropriate methodology for different asset classes
• Build and calibrate LGD models using historical default and recovery data, applying regression and segmentation techniques
• Quantify the impact of collateral type, seniority, and recovery timing on LGD estimates, including discount rate selection for cash flow recovery models
• Apply downturn LGD adjustments in line with Basel III IRB requirements and explain the regulatory rationale for through-the-cycle versus point-in-time calibration
• Calculate risk-weighted assets (RWA) and regulatory capital under the Foundation and Advanced IRB approaches using LGD as a key input
• Implement IFRS 9 lifetime LGD estimates for stage classification and expected credit loss (ECL) provisioning
• Design and execute back-testing and benchmarking exercises to validate LGD model performance and challenge model outputs
• Identify key sources of model risk in LGD estimation and apply best-practice governance and documentation standards
• Communicate LGD model assumptions, limitations, and results clearly to senior management, auditors, and regulators

Course Modules

Requirements & Prerequisites

Participants should have a working knowledge of financial statements, basic credit analysis principles, and how bank lending products are structured. Familiarity with Excel-based financial modelling and a basic understanding of statistics — including regression concepts — is strongly recommended. Prior exposure to banking regulation or risk management frameworks such as Basel or IFRS 9 is helpful but not required, as the course introduces regulatory context from first principles.

Training Methodology

• Worked numerical exercises using realistic loan portfolio datasets to build PD, LGD, and EAD estimates from scratch in Excel
• Case study analysis of real-world default and recovery events across retail mortgage, corporate, SME, and unsecured lending portfolios
• Regulatory document walkthroughs — participants annotate and interpret key sections of Basel III IRB guidelines and IFRS 9 application guidance
• Model-building workshops where participants construct and calibrate a segmented LGD model, then test its sensitivity to key assumptions
• Back-testing simulation exercises in which participants apply validation metrics (Gini, RMSE, bias tests) to pre-built model outputs and write a structured challenge memo
• Facilitated peer-review sessions where small groups critique each other's collateral valuation and recovery timing assumptions
• Scenario stress-testing exercises linking LGD estimates to macroeconomic downturn scenarios and calculating the resulting capital impact
• Structured reflection at the close of each day, prompting participants to map new learning to a specific challenge or model gap in their own institution

Organisational Benefits

• Stronger regulatory capital adequacy through more accurate IRB and standardised approach LGD inputs
• Reduced provisioning volatility by embedding robust, cycle-adjusted LGD estimates into IFRS 9 ECL models
• Improved lending decisions supported by a clearer understanding of expected loss and risk-adjusted return on capital (RAROC)
• Enhanced model governance and audit-readiness through standardised LGD documentation and validation practices
• Greater confidence in engaging with prudential supervisors, external auditors, and rating agencies on credit risk methodology
• Reduced regulatory risk and potential capital add-ons by demonstrating sound internal model practices
• Upskilled risk teams capable of independently building, updating, and challenging LGD models without reliance on external vendors
• Cross-functional alignment between credit, finance, and compliance teams on credit risk measurement standards

Where Is Credit Risk Measurement and Loss Given Default (LGD) Training Offered?

This course runs in-person across: Dubai, Pretoria, Abuja, Addis Ababa, Nairobi, Zanzibar, Kisumu, Arusha, Nakuru, Kigali, Cape Town, Accra, Naivasha, Lagos, Mombasa, Riyadh, Johannesburg, Kampala, Dar es Salaam, plus Live Virtual (online) cohorts. Browse live dates for your city below.

Upcoming Schedules

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