Yanping is a director in Moody’s Analytics quantitative research and modeling group, where she develops models and works with global clients on portfolio valuation and balance sheet analytics. She is currently focusing on models for IFRS 9 and CECL impairment accounting. Prior to joining Moody’s Analytics, Yanping worked on the treasury risk management advisory team at KPMG. She has a PhD in applied mathematics from Stanford University.
In this article, we use historical data to calculate and compare loan- and portfolio-level loss allowances under the incurred loss model and CECL.
IFRS 9 materially changes how institutions set aside loss allowance. With allowances flowing into earnings, the new rules can have dramatic effects on earnings volatility. In this paper, we propose general methodologies to measure and manage credit earnings volatility of a loan portfolio under IFRS 9. We walk through IFRS 9 rules and the different mechanisms that it interacts with which flow into earnings dynamics. We demonstrate that earnings will be impacted significantly by credit migration under IFRS 9. In addition, the increased sensitivity to migration will be further compounded by the impact of correlation and concentration. We propose a modeling framework that measures portfolio credit earnings volatility and discuss several metrics that can be used to better manage earnings risk.
Modeling the Joint Credit-Interest Rate Dynamics on a Multi-Dimensional Lattice Platform: Model Validation and Applications in Risk Integration
This document presents validation results for the credit-interest lattice or the multi-dimensional lattice (MDL) valuation model within Moody's Analytics RiskFrontier™.