Bernd Engelmann and Thi Thanh Lam Nguyen
This article aims to analyze the impact of COVID-19 measures by governments and central banks on International Financial Reporting Standards (IFRS) 9 loan loss provisions (LLPs)…
Abstract
Purpose
This article aims to analyze the impact of COVID-19 measures by governments and central banks on International Financial Reporting Standards (IFRS) 9 loan loss provisions (LLPs). Changes in the total amount of LLPs, distribution of outstanding loan balance among IFRS 9 stages and credit risk parameters used for calculation are investigated for each world region where banks report under IFRS.
Design/methodology/approach
Data for a global selection of 105 banks reporting under IFRS were collected from 2019 to 2020 annual reports, financial statements, and Pillar III reports. These data provide the basis to empirically analyze the impact of COVID-19 on LLPs.
Findings
In most world regions Stage 2 balances increase while Stage 3 balances remain comparatively stable. The credit risk parameters used for computing LLPs remained stable in 2020. However, in China, the impact of COVID-19 on banks was not detected. Mean Stage 1 balances for Chinese banks increased slightly during the pandemic. Aside from the COVID-19 impact, we find that LLPs, credit risk parameters, and loss absorption capacities are significantly lower for banks in Canada, Oceania and Western Europe compared to those in the rest of the world.
Originality/value
There exists previous research examining the COVID-19 impact on financial stability, implementation of emergency rules and country-wide analyses to anticipate default rates depending on recovery scenarios. However, this is the first global study on the immediate impact of COVID-19 on LLPs. It reveals the significant differences between world regions and provides implications about their resilience against future credit shocks.
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The purpose of this article is to derive formulas for lifetime expected credit loss of loans that are required for the calculation of loan loss reserves under IFRS 9. This is done…
Abstract
Purpose
The purpose of this article is to derive formulas for lifetime expected credit loss of loans that are required for the calculation of loan loss reserves under IFRS 9. This is done both for fixed-rate and floating rate loans under different assumptions on LGD modeling, prepayment, and discount rates.
Design/methodology/approach
This study provides exact formulas for lifetime expected credit loss derived analytically together with the mathematical proofs of each expression.
Findings
This articles shows that the formula most commonly applied in the literature for calculating lifetime expected credit loss is inconsistent with measuring expected loss based on expected discounted cash flows. Formulas based on discounted cash flows always lead to more conservative numbers.
Practical implications
For banks reporting under IFRS 9, the implication of this research is a better understanding of the different approaches used for computing lifetime expected loss, how they are connected, and what assumptions are underlying each approach. This may lead to corrections in existing frameworks to make applications of risk management systems more consistent.
Originality/value
While there is a lot of literature explaining IFRS 9 and evaluating its impact, none of the existing research has systematically analyzed the calculation of lifetime expected credit loss for this purpose and how the formula changes under different modeling assumptions. This gap is filled by this study.
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Keywords
Kerem Elibal and Eren Özceylan
The purpose of this paper is to conduct a systematic literature review for industry 4.0 maturity modeling research studies to obtain a clear view of the current state-of-the-art…
Abstract
Purpose
The purpose of this paper is to conduct a systematic literature review for industry 4.0 maturity modeling research studies to obtain a clear view of the current state-of-the-art. Identifying characteristics of the studies; gaps, limitations and highlighted features has been aimed to guide future research studies.
Design/methodology/approach
The study includes a systematic literature review conducted on Scopus, IEEE Xplore and Web of Science databases and 90 publications have been reviewed. A novel qualitative taxonomy has been constructed which aims to reduce the cognitive load of the readers.
Findings
While industry 4.0 maturity modeling is an emerging concept and taking researchers’ attraction, review studies are still in infancy. Current review papers are inadequate in getting a clear idea about the concept, especially from the perspective of guiding future researchers. By the conducted approach of classification conducted in this paper, it has been seen that there are some challenges for improving the industry 4.0 maturity modeling.
Research limitations/implications
Findings represented in this study can serve academicians and practitioners to develop and/or improve industry 4.0 maturity models.
Originality/value
The study includes a novel classification for the reviewed papers. Constructed taxonomy is among the first and tabular representations instead of prose analogy that aims to simplify the review of papers.