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Journal articles on the topic 'Expected Credit Loss'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Drin, Svitlana, and Fedir Serdiuk. "Expected credit loss modeling." Mohyla Mathematical Journal 6 (April 18, 2024): 14–19. http://dx.doi.org/10.18523/2617-70806202314-19.

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This article proposes a method for modeling the probability of default, describes the statistical evaluation of the model, and presents a model of the software implementation algorithm. The algorithm automatically selects from the group of regression models where the models are both linear regression and various modifications of semi-logarithmic models and lag models for macro factors Xi,t,Xi,t-1, ...,Xi,t-TStatistical analysis is carried out using the coefficient of determination R-squared, p-value, VIF (variance inflation factor).The relevance of this topic is determined by the need for bank

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2

Tarsicius Sunaryo. "Mengukur Risiko Kredit dengan Model Merton." JURNAL MANAJEMEN RISIKO 3, no. 1 (2022): 29–41. http://dx.doi.org/10.33541/mr.v3i1.4546.

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Abstract: Nilai perusahaan sama dengan penjumlahan nilai saham dan nilai utang (bond atau kewajiban) perusahaan. Nilai perusahaan berfluktuasi. Bila nilai perusahaan lebih kecil dibanding nilai bond perusahaan, maka perusahaan default. KMV menentukan bahwa titik default perusahaan sama dengan nilai utang jangka pendek dan setengah dari utang jangka panjangnya. Semakin tinggi nilai perusahaan, semakin kecil perusahaan default. KMV memetakan jarak dari nilai perusahaan ke titik default ke frekuensi default (expected default frequency). Keywords: risk/credit sensitive bond,leverage, probaility of

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3

Tenripada, Andi Sakinah Yan. "Application of Expected Loss (EL) for Loan Loss Estimation Based on Loan Term Using Simulation Data." International Journal of Mathematics, Statistics, and Computing 3, no. 1 (2025): 6–11. https://doi.org/10.46336/ijmsc.v3i1.179.

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This study aims to evaluate the effect of loan tenor on loan loss estimation using the Expected Loss (EL) model. Through this simulation data calculation, various scenarios with varying loan tenors show that loan tenors have a significant influence on the calculation of Expected Loss (EL). Longer tenors tend to increase the Expected Loss (EL) due to an increase in credit risk over time. The calculation results provide important implications for financial institutions in setting lending policies and managing credit risk.

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Gomaa, Mohamed, Kiridaran Kanagaretnam, Stuart Mestelman, and Mohamed Shehata. "Testing the Efficacy of Replacing the Incurred Credit Loss Model with the Expected Credit Loss Model." European Accounting Review 28, no. 2 (2018): 309–34. http://dx.doi.org/10.1080/09638180.2018.1449660.

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Bulantayev, A. M., K. B. Musakhan, A. N. Moldagulova та G. K. Sembina. "Прогноз ожидаемых убытков банка при предоставлении кредита". INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES 2, № 1(5) (2021): 145–49. http://dx.doi.org/10.54309/ijict.2021.05.1.019.

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This article uses the sample data of the SAS platform as an example to introduce the statisti-cal analysis and prediction of the expected loss of loans issued by banks. The original data for this study comes from a Kaggle source, which provides information about the credit history of bank customers. The technology is based on logistic regression, graphical data analysis, and the basis of building a model on the SAS platform. The model can be used to predict credit risk and describe credit risk in the banking system.

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Bank, Matthias, and Bernhard Eder. "Stufenzuordnung im Expected Credit Loss Model nach IFRS 9." Zeitschrift für das gesamte Bank- und Börsenwesen 66, no. 8 (2018): 544. http://dx.doi.org/10.47782/oeba201808054401.

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7

Philps, Daniel, and Solomon Peters. "Expected loss and fair value over the credit cycle." Journal of Credit Risk 1, no. 2 (2005): 35–49. http://dx.doi.org/10.21314/jcr.2005.011.

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8

Handorf, William C. "Implications of the Current Expected Credit Loss accounting model." Journal of Banking Regulation 19, no. 3 (2017): 211–21. http://dx.doi.org/10.1057/s41261-017-0047-y.

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9

Luo, Yibin. "Study of the Impact of Expected Credit Loss Model on the Quality of Accounting Information." BCP Business & Management 19 (May 31, 2022): 39–47. http://dx.doi.org/10.54691/bcpbm.v19i.655.

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In 2017, the Ministry of Finance issued a new standard on financial instruments to achieve convergence with international accounting standards, in which the emergence of expected credit loss model has great significance and far-reaching impact on the development of enterprises in China. In this paper, the impact of expected credit loss model on the quality of corporate accounting information is studied by using Differences-in-Differences method. Using accounting conservatism as a proxy variable for accounting information quality, this paper finds that the expected credit loss model can improve

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Brian Audika and Gideon Setyo Budiwitjaksono. "Expected Credit Loss Based on PSAK 71: A Systematic Literature Review." Proceedings of International Conference on Economics Business and Government Challenges 1, no. 1 (2022): 240–44. http://dx.doi.org/10.33005/ic-ebgc.v1i1.25.

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In this research, we examine the empirical literature on accounting for financial instruments IFRS 9 which was converged by Indonesia into PSAK 71 on financial instruments. We focus on three things, namely transition, impairment, and parameters in calculating expected credit loss (ECL). This research uses literature study method. This study aims to discuss the implementation of IFRS 9 or PSAK 71 on financial instruments in Indonesia from various literatures. We conclude that the ECL provisions affect on how financial instruments are valued and how the income statement affects the value of shar

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Kreienkamp, Tim, and Andrey Kateshov. "Credit Risk Modeling: Combining Classification And Regression Algorithms to Predict Expected Loss." Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438 8, no. 4 (2014): 4–10. http://dx.doi.org/10.17323/j.jcfr.2073-0438.8.4.2014.4-10.

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Credit risk assessment is of paramount importance in the financial industry. Machine learning techniques have been used successfully over the last two decades to predict the probability of loan default (PD). This way, credit decisions can be automated and risk can be reduced significantly. In the more recent parts, intensified regulatory requirements led to the need to include another parameter – loss given default (LGD), the share of the loan which cannot be recovered in case of loan default – in risk models. We aim to build a unified credit risk model by estimating both parameters jointly to

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Maurida, Zilfa Mau. "ANALISIS PENERAPAN EXPECTED CREDIT LOSS (ECL) TERHADAP PEMBENTUKAN CADANGAN KERUGIAN PENURUNAN NILAI MENURUT PSAK NO. 71 PADA LEMBAGA PEMBIAYAAN DI INDONESIA." Jurnal Akuntansi dan Keuangan 27, no. 2 (2022): 120–31. http://dx.doi.org/10.23960/jak.v27i2.373.

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This study aims to measure impairment losses (CKPN) before and adfter the application Expected Credit Loss (ECL method of PSAK 71, as well as the difference in net income before and after the application of the Expected Credit Loss (ECL) method according to PSAK 71 at financial institutions in Indonesia. The object of this research is sixteen financial institutions which are included in the sample criteria. This study uses a quantitative method by conducting a different type of Wilcoxon Signed t-test. Based on the different test results in the first and second hypotheses, the significance valu

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Hartanto, Ary Daniel, and Herlin Tundjung Setijaningsih. "DETERMINAN PROBABILITY OF DEFAULT DALAM PERHITUNGAN EXPECTED CREDIT LOSS PERBANKAN." Akurasi : Jurnal Studi Akuntansi dan Keuangan 6, no. 1 (2023): 157–76. http://dx.doi.org/10.29303/akurasi.v6i1.329.

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Penelitian ini bertujuan untuk menganalisis pengaruh profil risiko kredit, target pertumbuhan kredit dan makro ekonomi (PDB, nilai tukar dan inflasi) terhadap probabilitas gagal bayar dalam menghasilkan ekspektasi kerugian kredit sebagai diatur dalam PSAK 71. Penelitian dilakukan di PT Bank X selama pengamatan tahun 2016-2021 dengan analisis regresi linier berganda. Hasil penelitian ini menyatakan profil risiko kredit, target pertumbuhan kredit dan nilai tukar berpengaruh positif dan signifikan terhadap probability of default (PD), sedangkan PDB dan inflasi berpengaruh signifikan negatif terha

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Harris, Trevor S., Urooj Khan, and Doron Nissim. "The Expected Rate of Credit Losses on Banks' Loan Portfolios." Accounting Review 93, no. 5 (2018): 245–71. http://dx.doi.org/10.2308/accr-52012.

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ABSTRACT Estimating expected credit losses on banks' portfolios is difficult. The issue has become of increasing interest to academics and regulators with the FASB and IASB issuing new regulations for loan impairment. We develop a measure of the one-year-ahead expected rate of credit losses (ExpectedRCL) that combines various measures of credit risk disclosed by banks. It uses cross-sectional analyses to obtain coefficients for estimating each period's measure of expected credit losses. ExpectedRCL substantially outperforms net charge-offs in predicting one-year-ahead realized credit losses, a

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Shahari, Farihana, Roza Hazli Zakaria, and Md Saifur Rahman. "Investigation of the expected loss of sharia credit instruments in global Islamic banks." International Journal of Managerial Finance 11, no. 4 (2015): 503–12. http://dx.doi.org/10.1108/ijmf-12-2014-0196.

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Purpose – The purpose of this paper is to investigate the expected outcomes, both of positive and negative returns occurred by shariá credit instruments in global Islamic banks. The annual panel data from 2005 to 2012 is collected from 40 Islamic banks from 12 countries and value at risk (VaR) technique is employed in the investigation process. The findings of this study indicate several outcomes: first, majority of Islamic banks use debt-based financing (DBF) and avoid asset-based financing (ABF) due to the lack of secured rate of fixed returns and collateral. Second, the ABF financing shows

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Fleer, Sebastian. "Significant expected lifetime credit loss impairments: Determinants of bank loss recognition and stability implications." Journal of Accounting and Public Policy 51 (May 2025): 107305. https://doi.org/10.1016/j.jaccpubpol.2025.107305.

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Beatty, Anne, and Scott Liao. "What Do Analysts' Provision Forecasts Tell Us about Expected Credit Loss Recognition?" Accounting Review 96, no. 1 (2020): 1–21. http://dx.doi.org/10.2308/tar-2018-0049.

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ABSTRACT We document potential cross-sectional differences in how expected loss accounting will affect provision timeliness to provide important policy insights and contribute to the literature regarding the estimation of the expected loss model adoption impact and provision timeliness determinants. Our findings that analyst provision forecasts incrementally predict future nonperforming loans (NPLs) and market returns suggest that the incurred loss provision does not incorporate all available future loss information. Higher incremental coefficients on provision forecasts for banks with greater

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Resende, Miguel, Carla Carvalho, and Cecília Carmo. "Impacts of the Transition to the Expected Loss Model on the Portuguese Banking Sector." Journal of Risk and Financial Management 17, no. 4 (2024): 163. http://dx.doi.org/10.3390/jrfm17040163.

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This study addresses the implementation of the International Financial Reporting Standard 9 (IFRS 9) in the European Union as of 1 January 2018, replacing the International Accounting Standard 39 (IAS 39) to introduce a new model for recognizing Loan Loss Provisions (LLP), based on Expected Credit Loss (ECL). This model responds to criticisms of the former Incurred Credit Loss (ICL) system for its inability to reflect credit losses in a timely manner, potentially exacerbating the effects of financial crises. This study focuses on the effects of adopting the ECL model on the level of Loan Loss

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Septian, Bayu Kristanto. "Did Expected Credit Loss Fair for Indonesian Banks in COVID-19?" International Journal of Innovation, Creativity and Change 15, no. 2 (2021): 966–71. https://doi.org/10.5281/zenodo.4539688.

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In this paper, we explore the impact of the COVID-19 crisis on the accounting practices associated with the Expected Credit Loss (ECL) approach by Peryataan Standar Akuntasi Keuangan (PSAK) 71. Given the complexity of the pandemic, the neutral application of existing accounting standards is of more importance than ever as it ensures objective decision-useful information that serves comparability, maintenance of a level playing field and transparency. Worldwide interventions by banking regulators, however, have considerable potential to interfere with these fundamental contributions of financia

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Fawzi Shubita, Mohammad, Faez Hlail Srayyih, Sinan Abdullah Harjan, Dua’a Shubita, and Majd Munir Iskandrani. "Assessing the impact of IFRS 9’s Expected Credit Loss model on capital allocation in Jordanian banks." Banks and Bank Systems 20, no. 2 (2025): 83–94. https://doi.org/10.21511/bbs.20(2).2025.07.

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This study investigates the empirical effects of implementing the Expected Credit Loss (ECL) model under IFRS 9 on capital budgeting decisions within the Jordanian banking sector. The analysis is based on a full population of all 13 Jordanian commercial banks listed on the Amman Stock Exchange from 2013 to 2023. Using panel data regression models, the study evaluates changes in three key financial ratios: Capital to Assets (CA), Equity to Assets (EA), and Loans to Assets (LA).The findings reveal that adopting the ECL model led to a statistically significant increase in CA by 0.3% (p = 0.04), s

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Filusch, Tobias, and Sascha H. Mölls. "„(Lifetime) Expected Credit Losses“ im Rahmen der IFRS-Rechnungslegung." Zeitschrift für das gesamte Genossenschaftswesen 67, no. 4 (2017): 245–62. http://dx.doi.org/10.1515/zfgg-2017-0025.

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ZusammenfassungMit dem „(Lifetime) Expected Credit Loss“ hat der internationale Standardsetzer einen prospektiven Wertminderungsmaßstab für Finanzinstrumente entwickelt. Mit Blick auf die dadurch induzierte Stärkung des Gläubigerschutzes sowie eine mögliche Angleichung des deutschen HGB an die Vorgaben der IFRS sollten sich Banken und Versicherungen im genossenschaftlichen Umfeld ebenso wie Prüfungsverbände frühzeitig ein Bild von den anstehenden Änderungen machen.

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Musiiets, Tetianа, Iryna Olshevska, and Valeriia Mozhna. "Expected credit losses in international banking business." Scientific notes, no. 35 (June 24, 2024): 94–113. http://dx.doi.org/10.33111/vz_kneu.35.24.02.09.061.067.

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The late and insufficient formation of provisions for credit losses became one of the causes of the global financial crisis of 2008-2009. In response to the challenges posed to the international community by this crisis, the Basel Committee on Banking Supervision developed Basel III requirements for financial institutions, which include including issues of credit risk assessment. The International Financial Reporting Standards Board has completely revised its vision of credit risk assessment approaches and issued a new standard, IFRS 9 Financial Instruments. However, Basel III and IFRS 9 form

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Macchioni, Riccardo, Alessandra Allini, and Martina Prisco. "Expected credit losses and managerial discretion. Current practices and future challenges." MANAGEMENT CONTROL, no. 3 (November 2021): 111–34. http://dx.doi.org/10.3280/maco2021-003006.

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This paper examines the loan loss provisioning behaviour during the transition from IAS 39 to IFRS 9 for a sample of 403 banks in 27 countries in European Union. The objective of the study is to investigate whether during the first years of adoption of the new expected credit loss (ECL) impairment model banks are more en-couraged to smooth earnings and manage capital, compared to the previous in-curred loss (ICL) model. Results show that under ECL, banks adopt a more ag-gressive opportunistic behaviour in accordance with the income-smoothing and capital management approach. Management should b

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Kim, Sehwa, Seil Kim, Anya Kleymenova, and Rongchen Li. "Current Expected Credit Losses (CECL) Standard and Banks' Information Production." Finance and Economics Discussion Series, no. 2023-063 (September 2023): 1–108. http://dx.doi.org/10.17016/feds.2023.063.

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We examine whether the adoption of the current expected credit losses (CECL) model, which reflects forward-looking information in loan loss provisions (LLP), improves banks’ information production. Consistent with better information production, we find changes in CECL banks' financial reporting and operations. First, these banks' loan loss provisions become timelier and better reflect future local economic conditions. Second, CECL banks disclose longer, more forward-looking, and more quantitative LLP information. Lastly, they have fewer loan defaults after adopting CECL. These improvements are

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Liu, Zilong, Hongyan Liang, and Chang Liu. "Macroeconomic Determinants of the Credit Loss Forecasting." Journal of Finance Issues 23, no. 1 (2025): 36–58. https://doi.org/10.58886/jfi.v23i1.9097.

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Macroeconomic variables are crucial inputs used in the credit loss forecasting (LF) models and the use of macro effects is also mandated by regulators for stress testing purposes which allow banks to project the potential credit loss under different hypothetical macroeconomic scenarios. The COVID-19 pandemic has caused an unprecedented level of volatility in the macroeconomic variables, leading to new challenges to use macroeconomic variables in the LF and the current expected credit loss (CECL) modeling framework. Especially, the historical observed strong relationship between the macroeconom

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Ibrahim, Mohammed. "A Propsed Framework to Audit of Expected credit loss "ECL" Estimate Uncertainty." مجلة الدراسات والبحوث التجارية 3, no. 3 (2020): 393–424. https://doi.org/10.21608/jcsr.2020.400234.

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Jacobs, Michael. "A Holistic Model Validation Framework for Current Expected Credit Loss (CECL) Model Development and Implementation." International Journal of Financial Studies 8, no. 2 (2020): 27. http://dx.doi.org/10.3390/ijfs8020027.

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The Current Expected Credit Loss (CECL) revised accounting standard for credit loss provisioning is the most important change to United States (US) accounting standards in recent history. In this study, we survey and assess practices in the validation of models that support CECL, across dimensions of both model development and model implementation. On the development side, this entails the usual SR 11-7 aspects of model validation; however, highlighted in the CECL context is the impact of several key modeling assumptions upon loan loss provisions. We also consider the validation of CECL model

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Gubareva, Mariya. "How to estimate expected credit losses – ECL – for provisioning under IFRS 9." Journal of Risk Finance 22, no. 2 (2021): 169–90. http://dx.doi.org/10.1108/jrf-05-2020-0094.

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PurposeThis paper provides an objective approach based on available market information capable of reducing subjectivity, inherently present in the process of expected loss provisioning under the IFRS 9.Design/methodology/approachThis paper develops the two-step methodology. Calibrating the Credit Default Swap (CDS)-implied default probabilities to the through-the-cycle default frequencies provides average weights of default component in the spread for each forward term. Then, the impairment provisions are calculated for a sample of investment grade and high yield obligors by distilling their p

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Milonas, Natasa, and Gary van Vuuren. "Simulating Credit Loss Distributions: Empirical Versus the Vasicek Model." International Journal of Economics and Financial Issues 14, no. 2 (2024): 77–88. http://dx.doi.org/10.32479/ijefi.15698.

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Because credit losses can be substantial, managing credit risk is a focus area of risk measurement and management. It is important for financial institutions to select credit risk models that accurately forecast losses. The Basel Committee on Banking Supervision (BCBS) chose the closed-form single risk factor Vasicek model for regulatory capital calculations. In this article, its forecast accuracy is compared with empirical loss distributions using simulated probabilities of default and losses given default. The effect of altering probabilities of default on asset correlations was analysed and

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Gubareva, Mariya. "Weight of the Default Component of CDS Spreads: Avoiding Procyclicality in Credit Loss Provisioning Framework." Complexity 2019 (July 4, 2019): 1–19. http://dx.doi.org/10.1155/2019/7820618.

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The current expected loss calculations have recently attracted considerable attention in the research on credit risk modeling, impairment provisioning, and financial networks’ stability. A new CDS-based approach to estimate current expected credit loss is proposed for low default portfolios, containing credit exposures to corporate issuers covered by publicly traded CDS contracts. First, a fraction of CDS spread related to a pure default compensation for different CDS maturities is assessed. Our results contrast with previous research. Second, based on the obtained historical weights of the de

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Vasilyeva, Alfiya, and Elvina Frolova. "Methods of Calculation of Expected Credit Losses Under Requirements of IFRS 9." Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438 13, no. 4 (2019): 74–86. http://dx.doi.org/10.17323/j.jcfr.2073-0438.13.4.2019.74-86.

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The most important area of work for financial market regulators including International Accounting Standards Board is to clarify the metrics of credit assessment. This problem became particularly relevant after the financial crisis of 2008, when the insolvency of approaches to the assessment of credit risks adopted under the then international financial reporting standard IFRS (IAS) 39 became apparent, since credit losses on financial instruments were taken into account by the “loss model”, and therefore, the asset was recognized as financially impaired due to the fact of credit quality deteri

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Guamán-Chumaina, María Mercedes, and Lenyn Geovanny Vásconez-Acuña. "Deterioro de la cartera de crédito en las COAC: métodos y normativas aplicables en Ecuador." Revista Metropolitana de Ciencias Aplicadas 7, S2 (2024): 108–21. http://dx.doi.org/10.62452/1p21z849.

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This study focused on analyzing accounting and regulatory practices related to bad debt loss management in credit unions in Ecuador. A mixed research approach was used, combining quantitative and qualitative methods. Most institutions use the Expected Loss Provisioning (EPL) method and consider the use of historical data to calculate expected losses in the loan portfolio to be important. In addition, there is a trend towards comprehensive credit risk assessment, including qualitative and quantitative factors. The quality and reliability of financial information, together with regulatory compli

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Lieus, Hansen Juni, Devin Tedja, Vanessa Joewita, Agus Sofian Eka Hidayat, and Alexander R. J. Silalahi. "APPLICATION OF EXPECTED CREDIT LOSS MODEL AND MARKOV CHAIN TO CALCULATE NET SINGLE PREMIUM OF UNSECURED CREDIT INSURANCE." BAREKENG: Jurnal Ilmu Matematika dan Terapan 17, no. 4 (2023): 2161–70. http://dx.doi.org/10.30598/barekengvol17iss4pp2161-2170.

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Transferring credit risk to an insurance company is a way to mitigate risk. Premiums should be calculated accurately to attain economic value for both the lender and the guarantor. The aim of this study was to determine the net single premium (NSP) values for an unsecured credit insurance product using the expected credit loss (ECL) method from IFRS 9. This study used data generated through simulation of insurance policies issued in 2015 or 2016. Their state classifications were monthly observed from 2016 to 2020. The probability of disbursed claim (PDC) parameter replaced the probability of d

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陈, 雪锦. "Comparative Analysis of Expected Credit Loss Models for Accounts Receivable at Different Ages." Frontiers of International Accounting 13, no. 05 (2024): 717–21. http://dx.doi.org/10.12677/fia.2024.135092.

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Meilani, Any. "PENERAPAN METODE CREDITRISK+ DALAM PENGUKURAN RISIKO KREDIT KENDARAAN BERMOTOR (KASUS PADA PT X)." Jurnal Organisasi dan Manajemen 6, no. 2 (2010): 101–18. http://dx.doi.org/10.33830/jom.v6i2.286.2010.

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Identify and measure credit risk by using a method in accordance with the characteristics of finance companies is one of a prudent first step in minimizing potential losses. Potential losses can be seen from the Non Performing Loan (NPL) and recovery rate of the company. Credit risk measurement remains important as preventive and anticipatory measures for a finance company in managing the potential consumer default in fulfilling their obligations. By using 36 months of credit risk in motor vehicles (2006-2008) which includes the number of units of motor vehicles, the amount of exposure, collec

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Brouwer, Tristan, Job Huttenhuis, and Hoeven Ralph ter. "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 95, no. (11/12) (2021): 381–96. https://doi.org/10.5117/mab.95.75980.

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This study examines the provision for credit losses and its disclosures for Global Systemically Important Banks (G-SIBs) in connection to the COVID-19 crisis. We find a profound difference in the increase of the provision for credit losses between banks that report under IFRS and US GAAP. For banks that report under US GAAP, the provision for credit losses more than doubles, while it increases by only 32 percent for banks that report under IFRS. This difference becomes even more striking when considering that the increase for IFRS-reporting banks is partly attributable to increased lending act

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Volarević, Hrvoje, and Mario Varović. "Internal model for IFRS 9 - Expected credit losses calculation." Ekonomski pregled 69, no. 3 (2018): 269–97. http://dx.doi.org/10.32910/ep.69.3.4.

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This article explores and analyzes the implementation problem of International Financial Reporting Standard 9 (IFRS 9) which is in use from 1 January 2018. IFRS 9 is most relevant for financial institutions, but also for all business subjects with a significant share of financial assets in their Balance sheet. The main objective of this article is the implementation of new impairment model for financial instruments, which is measurable through Expected Credit Losses (ECL). The use of this model is in correlation with a credit risk of the company for which it is necessary to determine basic var

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Al-Nsour, Rania, and Murad Abuaddous. "A Comparison Study between IFRS 9 and IAS 39 in GCC Countries." European Journal of Business and Management Research 7, no. 6 (2022): 7–13. http://dx.doi.org/10.24018/ejbmr.2022.7.6.1687.

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IFRS 9 was introduced as a replacement for IAS 39, which spurred a wide debate since its implementation. This study aims to show the impact of IFRS 9 on the performance, solvency, credit ratio, capital adequacy ratio, expected credit loss, non-performing credits and write-offs for local banks operating within the Gulf Cooperation Council. To achieve the objectives of this study, data from financial disclosures was collected for 53 GCC banks for the period 2012-2020, which had 477 years of observation. The cross-sectional data was analyzed using the logit model (panel logistic regression model)

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Hanus, I., I. Plikus, and T. Zhukova. "DEBTOR RATING AS A TOOL OF DEBT MANAGEMENT." Vìsnik Sumsʹkogo deržavnogo unìversitetu, no. 3 (2020): 121–29. http://dx.doi.org/10.21272/1817-9215.2020.3-13.

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IFRS 9 “Financial Instruments” introduced a new model of impairment based on expected credit losses, in which the impairment is based on expected credit losses, and the provision for losses is recognized before the credit loss, i.e. companies recognize losses immediately after initial recognition of the financial asset and revise the amount of the provision for expected credit losses at the reporting date. To create a provision for credit losses, IFRS 9 allows using several practical tools, including the rating debtors’ method. However, IFRS 9 does not express a clear opinion on how the expect

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Rozmetova, Umida Yuldashevna. "MONITORING OF CREDIT RISKS AS FINANCIAL RESOURCES IN COMMERCIAL BANKS." International journal of trends in business administration International journal of trends in business administration 12, no. 1 (2022): 106–11. https://doi.org/10.5281/zenodo.6683264.

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Credit risk analysis can be thought of as an extension of the credit allocation process. After an individual or business applies to a bank or financial institution for a loan, the lending institution analyzes the potential benefits and costs associated with the loan. Credit risk analysis is used to estimate the costs associated with the loan. Credit risk or credit default risk associated with a financial transaction is simply the expected loss of that transaction. In commercial banks, risk has always been one of the most basic concepts. This article examines the measurement and monitoring of t

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Rafika Sari and Yevi Dwitayanti. "The Analysis of Changes in Implementation to PSAK 71 Post-Covid 2019 on Allowance for Impairment Losses (In BUMN Banking Sector Companies Listed on the IDX)." Jurnal Akuntansi 13, no. 3 (2023): 177–86. http://dx.doi.org/10.33369/jakuntansi.13.3.177-186.

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Changes in the Statement of Financial Accounting Standards from PSAK 55 to PSAK 71 require banks to use the Expected Credit Loss (ECL) method for the establishment of Allowance for Impairment Losses (CKPN). In the ECL method, banks establish CKPN from the beginning of credit recognition using the forward-looking method on macroeconomic conditions. In Indonesia's current status quo in facing the Covid-19 pandemic, the existence of PSAK has begun to be tested, adjustments must be made to financial accounting standards that are useful for strengthening the line of corporate accountability in Indo

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Bojar, Paweł, and Małgorzata Anna Olszak. "The Impact of IFRS 9 on the Link Between Lending and the Capital Ratio in Publicly Traded Banks in Poland." Journal of Banking and Financial Economics 2022, no. 1(17) (2022): 60–73. http://dx.doi.org/10.7172/2353-6845.jbfe.2022.1.4.

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This paper aims to determine the role of the expected credit loss approach as defined in IFRS 9 in the effects of capital ratio on loans growth in publicly traded banks in Poland. To resolve this problem, we apply semi-annual data of individual banks in 2012–2018. Using several estimation techniques, we find that in the period of implementation of the expected credit loss approach, the links between loans growth and the capital ratio were enhanced. In particular, lending growth is more sensitive to levels of the capital ratio. These results are important with respect to the goal of bank financ

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Dithasya Anava Syabani Anissa, Tommy Kuncara, and Bernardus Wishman S. Siregar. "ANALYSIS OF IMPLEMENTATION OF PSAK 71 AGAINST RESERVE LOSS OF IMPAIRMENT WHEN COVID-19 PANDEMIC IN PT. BANK CENTRAL ASIA TBK." International Journal Management and Economic 1, no. 2 (2022): 14–22. http://dx.doi.org/10.56127/ijme.v1i2.150.

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This study aims to analyze the implementation of PSAK 71 against impairment loss reserves during the Covid-19 pandemic in banking. The object of research on scientific writing is PT. Bank Central Asia Tbk. The types of data used in this research are qualitative and quantitative data. Sources of data used in this study is secondary data obtained from the company's official website. The data collection techniques used are literature studies and documentation techniques in the form of financial statements of PT. Bank Central Asia Tbk 2020. The results of this study showed that the bank has implem

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Dithasya Anava Syabani Anissa, Tommy Kuncara, and Bernardus Wishman S. Siregar. "ANALYSIS OF IMPLEMENTATION OF PSAK 71 AGAINST RESERVE LOSS OF IMPAIRMENT WHEN COVID-19 PANDEMIC IN PT. BANK CENTRAL ASIA TBK." International Journal Management and Economic 1, no. 2 (2022): 14–22. http://dx.doi.org/10.56127/jaemb.v1i2.150.

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This study aims to analyze the implementation of PSAK 71 against impairment loss reserves during the Covid-19 pandemic in banking. The object of research on scientific writing is PT. Bank Central Asia Tbk. The types of data used in this research are qualitative and quantitative data. Sources of data used in this study is secondary data obtained from the company's official website. The data collection techniques used are literature studies and documentation techniques in the form of financial statements of PT. Bank Central Asia Tbk 2020. The results of this study showed that the bank has implem

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Dithasya Anava Syabani Anissa, Tommy Kuncara, and Bernardus Wishman S. Siregar. "ANALYSIS OF IMPLEMENTATION OF PSAK 71 AGAINST RESERVE LOSS OF IMPAIRMENT WHEN COVID-19 PANDEMIC IN PT. BANK CENTRAL ASIA TBK." International Journal Management and Economic 1, no. 2 (2022): 14–22. http://dx.doi.org/10.56127/jaemb.v1i2.150.

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This study aims to analyze the implementation of PSAK 71 against impairment loss reserves during the Covid-19 pandemic in banking. The object of research on scientific writing is PT. Bank Central Asia Tbk. The types of data used in this research are qualitative and quantitative data. Sources of data used in this study is secondary data obtained from the company's official website. The data collection techniques used are literature studies and documentation techniques in the form of financial statements of PT. Bank Central Asia Tbk 2020. The results of this study showed that the bank has implem

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Morshed, Amer, Mohammed Daoud Othman, and Asma’a Al-Amarneh. "Investigating the applicability of the expected credit loss model to Islamic Sukuk: Law aspects." Corporate Law and Governance Review 6, no. 3 (2024): 81–89. http://dx.doi.org/10.22495/clgrv6i3p9.

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This paper examines the application of the expected credit loss (ECL) model under International Financial Reporting Standards (IFRS) 9 to Islamic Sukuk, which indicates that accountants do not regard any gap between Islamic financial instruments and IFRS. Since Sukuk have special features according to Islamic finance, such as the non-usage of interest (riba) and risk-sharing, this paper reviews the issues and possible modifications that may be required for their compliance with both Sharia and international accounting standards. Applying a mixed-methods approach, 30 experts in Islamic finance

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Yadav, Mohini. "Impact of current expected credit loss (CECL) on the US financial institutions – An overview." Journal of Management Research and Analysis 6, no. 2 (2019): 85–87. http://dx.doi.org/10.18231/j.jmra.2019.015.

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Sanfins, Marco Aurélio, Beatriz Jardim Pina Rodrigues, Daiane Rodrigues dos Santos, and Raphael Oliveira Lourenço. "Credit Risk Calculation: An Application in the Brazilian Market Using the CreditRisk+ Model with Uncertainties." International Business Research 13, no. 1 (2019): 40. http://dx.doi.org/10.5539/ibr.v13n1p40.

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Due to an increasing economic instability worldwide, financial institutions are demanding more robust and powerful methodologies of credit risk modeling in order to ensure their financial health. The statistical model CreditRisk+, developed by Credit Suisse Financial Products (CSFP), is widely spread in the insurance market since it is not necessary to make assumptions. This is because the model is based on the default risk, that is, non-payment risk. The main goal of the above-mentioned model is to measure expected and non-expected losses in a credit portfolio. In order to measure default eve

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Callen, Jeffrey L., Sean W. G. Robb, and Dan Segal. "Revenue Manipulation and Restatements by Loss Firms." AUDITING: A Journal of Practice & Theory 27, no. 2 (2008): 1–29. http://dx.doi.org/10.2308/aud.2008.27.2.1.

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SUMMARY: This paper investigates the relation between the extent of a firm’s past and expected future losses or negative cash flows and the ex ante probability that it will manipulate revenues. When a firm has a string of losses or negative cash flows, traditional valuation models do not yield reliable estimates of firm value, and traditional price-earnings ratios are not meaningful. Evidence suggests that market participants tend to value loss firms on the basis of the level and growth in revenues, rather than cash flows and earnings, thereby motivating these firms to overstate revenue. In fa

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Van Vuuren, Gary, Riaan De Jongh, and Tanja Verster. "The Impact Of PD-LGD Correlation On Expected Loss And Economic Capital." International Business & Economics Research Journal (IBER) 16, no. 3 (2017): 157–70. http://dx.doi.org/10.19030/iber.v16i3.9975.

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The Basel regulatory credit risk rules for expected losses require banks use downturn loss given default (LGD) estimates because the correlation between the probability of default (PD) and LGD is not captured, even though this has been repeatedly demonstrated by empirical research. A model is examined which captures this correlation using empirically-observed default frequencies and simulated LGD and default data of a loan portfolio. The model is tested under various conditions dictated by input parameters. Having established an estimate of the impact on expected losses, it is speculated that

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