Problem
Research questions and friction points this paper is trying to address.
Loss Given Default (LGD)
Credit Cards
Run-off Triangles
Regression Model
IFRS 9
Comparing two approaches for modelling the loss given default of credit cards: Run-off triangles vs regression
🤖 AI Summary
This study addresses the limitations of the traditional rolling triangle method in estimating Loss Given Default (LGD) for credit cards, specifically its insufficient accuracy and inability to recover U-shaped distributions. Within the IFRS 9 framework, this work systematically compares the predictive performance of the rolling triangle approach against regression models. The empirical analysis employs a two-stage regression modeling strategy, data-driven diagnostic techniques, and time-series aggregation comparisons. Results demonstrate that the two-stage regression model more accurately captures empirical trends, achieving significantly superior predictive precision compared to the conventional rolling triangle method. These findings provide robust methodological support and practical guidance for LGD modeling in credit risk management.
📝 Abstract
The use of run-off triangles (ROTs) is a common industry practice in estimating the loss given default (LGD) risk parameter when predicting credit losses in banking. We benchmark this industry practice using credit card data against a more sophisticated (though classical) regression-based approach, which is able to leverage various types of input variables in producing loan-level LGD-estimates. This regression-based approach can demonstrably recover the typical characteristics of the'U-shaped'empirical LGD-distribution, which the ROT-based approach cannot do. First, we critically review the ROT-based approach and identify multiple demerits using data-driven diagnostics. We then estimate a two-stage regression-based LGD-model and favourably assess the model performance of each component (or'stage'). Finally, we aggregate the LGD-estimates produced by each approach over time, and compare each time series to the mean empirical loss rate over time. The ROT-based aggregates diverge substantially from the empirical rate over most time periods, whilst the regression-based aggregates follow the empirical trends much closer. These results underscore the greater prediction accuracy of the regression-based LGD-model, relative to the ROT-based one. By implication, the former approach is probably better than the latter ROT-based approach when estimating the LGD under the IFRS 9 accounting framework, which prioritises accuracy.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Loss Given Default (LGD)
Run-off Triangles
Two-stage Regression Model
Credit Card Modelling
IFRS 9
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