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Switching from Incurred to Expected Loan Loss Provisioning: Early Evidence

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  • GERMÁN LÓPEZ‐ESPINOSA
  • GAIZKA ORMAZABAL
  • YUKI SAKASAI

Abstract

This paper provides early evidence on the effect of global regulation mandating a switch from loan loss provisioning (LLP) based on incurred credit losses (ICLs) to LLP based on expected credit losses (ECLs). Using a sample of systemically important banks from 74 countries, we find that ECL provisions are more predictive of future bank risk than ICL provisions. Corroborating that the switch to ECL provisioning results in more information to assess bank risk, we also observe that the announcement of a larger first‐time impact of the accounting change elicits lower stock returns and higher changes in credit default swap spreads. Critically, these patterns are most pronounced when credit conditions deteriorate. Additional analyses show that the higher information content of the ECL model stems from the provisions for nondefaulted loans, which did not exist under ICL. Our study contributes to the debate on the effect of the ECL model on procyclicality, an especially pressing issue in the context of the current pandemic.

Suggested Citation

  • Germán López‐Espinosa & Gaizka Ormazabal & Yuki Sakasai, 2021. "Switching from Incurred to Expected Loan Loss Provisioning: Early Evidence," Journal of Accounting Research, Wiley Blackwell, vol. 59(3), pages 757-804, June.
    • Handle: RePEc:bla:joares:v:59:y:2021:i:3:p:757-804
    DOI: 10.1111/1475-679X.12354
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    Cited by:

    1. Sehwa Kim & Seil Kim & Anya V. Kleymenova & Rongchen Li, 2023. "Current Expected Credit Losses (CECL) Standard and Banks' Information Production," Finance and Economics Discussion Series 2023-063, Board of Governors of the Federal Reserve System (U.S.).
    2. Miguel Resende & Carla Carvalho & Cecília Carmo, 2024. "Impacts of the Expected Credit Loss Model on Pro-Cyclicality, Earnings Management, and Equity Management in the Portuguese Banking Sector," JRFM, MDPI, vol. 17(3), pages 1-19, March.
    3. Ren, Meixu & Ke, Konglin & Yu, Xin & Zhao, Jinxuan, 2023. "Local governments' economic growth target pressure and bank loan loss provision: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 1-14.
    4. Cascino, Stefano & Daske, Holger & Defond, Mark & Florou, Annita & Gassen, Joachim & Hung, Mingyi, 2023. "Reflections on the 20-year anniversary of worldwide IFRS adoption," LSE Research Online Documents on Economics 120205, London School of Economics and Political Science, LSE Library.
    5. Ghosh, Saibal, 2022. "Elections and provisioning behavior: Assessing the Indian evidence," Economic Systems, Elsevier, vol. 46(1).
    6. Tristan Brouwer & Job Huttenhuis & Ralph ter Hoeven, 2021. "Empirical results for expected credit losses of G-SIBs during COVID-19. The proof of the pudding is in the eating," Maandblad Voor Accountancy en Bedrijfseconomie Articles, Maandblad Voor Accountancy en Bedrijfseconomie, vol. 95(11-12), pages 381-396, December.
    7. Salazar, Yadira & Merello, Paloma & Zorio-Grima, Ana, 2023. "IFRS 9, banking risk and COVID-19: Evidence from Europe," Finance Research Letters, Elsevier, vol. 56(C).
    8. Lucas Mahieux & Haresh Sapra & Gaoqing Zhang, 2023. "CECL: Timely Loan Loss Provisioning and Bank Regulation," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 3-46, March.
    9. Bischof, Jannis & Haselmann, Rainer & Kohl, Frederik & Schlueter, Oliver, 2022. "Limitations of implementing an expected credit loss model," LawFin Working Paper Series 48, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    10. Arianna Spina Pinello & Ernest Lee Puschaver, 2023. "Does Current Expected Credit Loss Accounting Reflect A Best Estimate? Time Series Evidence From Credit Loss Reporting," Accounting & Taxation, The Institute for Business and Finance Research, vol. 15(1), pages 83-103.

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