CSRSA Live Webinar: Scenario-Driven Expected Credit Loss: Incorporating Climate and Sectoral Risk into Provisioning Models
Title: Scenario-Driven Expected Credit Loss: Incorporating Climate and Sectoral Risk into Provisioning Models
Date: April 29, 2026 @ 1PM-2PM Eastern Time
Presenter: Mahmood Alaghmandan Manager, Model Validation and Risk Management at Farm Credit Canada
Integrating scenario analysis into expected credit loss (ECL) frameworks such as IFRS 9 and CECL represents an important evolution in credit risk measurement. Traditionally, provisioning models have been used to estimate forward-looking losses under probability-weighted macroeconomic conditions. However, these same frameworks can also serve as powerful tools for assessing the impact of structured scenarios ,including macroeconomic shocks, policy changes, and climate transition or physical risks, on credit portfolios. By translating scenario narratives into adjustments to key risk drivers such as probability of default (PD) and, where appropriate, loss given default (LGD), institutions can produce consistent, forward-looking estimates of portfolio vulnerability.
For credit risk management, this approach is significant because it bridges accounting-based provisioning, stress testing, and scenario analytics within a single coherent framework. It enables institutions to move beyond high-level macro stress overlays and instead incorporate sectoral and exposure-level differentiation, capturing heterogeneous impacts across industries, regions, and credit quality segments. As regulatory expectations increasingly emphasize climate and other emerging risks, embedding scenario analysis directly into ECL methodologies provides a practical, scalable, and governance-aligned solution for measuring and managing credit risk under uncertainty.
Price: Free for members
Presenter Profile: Mahmood Alaghmandan
Mahmood Alaghmandan is Manager, Model Validation and Risk Management at Farm Credit Canada, specializing in credit risk modelling, model validation, stress testing, and scenario analysis within regulated financial institutions. His work focuses on IFRS 9 expected credit loss (ECL) frameworks, probability of default modelling, and the integration of forward-looking macroeconomic and climate scenarios into credit risk measurement.
Mahmood was a principal designer of key methodological components of the Standardized Climate Scenario Exercise (SCSE) conducted by OSFI and Québec’s AMF. His research and professional work bridge sustainability risk and traditional financial risk management, with particular emphasis on developing practical, scalable approaches for measuring scenario impacts on credit portfolios.
