Moving toward the expected credit loss model under IFRS 9: capital transitional arrangement and bank systematic risk
Bibliographic record
Abstract
This paper examines banks’ option to adopt the capital transitional arrangement (CTA) set out by the Basel Committee on Banking Supervision, in response to the introduction of the International Financial Reporting Standard 9 (IFRS 9), which requires the use of an expected credit loss model instead of an incurred loss model to estimate the impairment of financial assets. Using a sample of publicly listed European banks from 2016 to 2019, we find that bank CTA adoption choice is associated with neutral factors captured by bank-specific fundamental characteristics, and potential opportunistic factors related to regulatory constraints implied by the application of IFRS 9. We further find that banks that adopted the CTA (CTA adopters) decrease their exposure to systematic risk during the transitional period. However, this relationship is only significant in countries with powerful banking authorities. In those with less powerful banking authorities, CTA adopters tend to exercise more aggressively their accounting discretion. Our study is the first to address banks’ voluntary choice to adopt the CTA policy under the mandatory application of IFRS 9.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".