Relevant bibliographies by topics / Expected Credit Loss

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Expected Credit Loss'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Expected Credit Loss"

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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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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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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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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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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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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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Dissertations / Theses on the topic "Expected Credit Loss"

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Malwandla, Musa. "Loss distributions in consumer credit risk : macroeconomic models for expected and unexpected loss." Master's thesis, University of Cape Town, 2016. http://hdl.handle.net/11427/20414.

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This thesis focuses on modelling the distributions of loss in consumer credit arrangements, both at an individual level and at a portfolio level, and how these might be influenced by loan-specific factors and economic factors. The thesis primarily aims to examine how these factors can be incorporated into a credit risk model through logistic regression models and threshold regression models. Considering the fact that the specification of a credit risk model is influenced by its purpose, the thesis considers the IFRS 7 and IFRS 9 accounting requirements for impairment disclosure as well as Bas
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Starlander, Isak. "Counterparty Credit Risk on the Blockchain." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215493.

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Counterparty credit risk is present in trades offinancial obligations. This master thesis investigates the up and comingtechnology blockchain and how it could be used to mitigate counterparty creditrisk. The study intends to cover essentials of the mathematical model expectedloss, along with an introduction to the blockchain technology. After modellinga simple smart contract and using historical financial data, it was evidentthat there is a possible opportunity to reduce counterparty credit risk withthe use of blockchain. From the market study of this thesis, it is obvious thatthe current fina
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Krüger, Steffen Verfasser], and Daniel [Akademischer Betreuer] [Rösch. "Advanced Dependency Modeling in Credit Risk - Lessons for Loss Given Default, Lifetime Expected Loss and Bank Capital Requirements / Steffen Krüger ; Betreuer: Daniel Rösch." Regensburg : Universitätsbibliothek Regensburg, 2017. http://d-nb.info/1139892398/34.

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Fjellstedt, Hanna, and Daniel Fischer. "IFRS 9 Finansiella instrument : Vilken effekt den nya regleringen har på svenska banker efter införandet." Thesis, Högskolan Dalarna, Företagsekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:du-30762.

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Bakgrund: En ny reglering har införts den 1 januari 2018, vilket är IFRS 9 finansiella instrument som ersätter IAS 39. Värdering och redovisning förändras från en objektiv till en subjektiv bedömning av kreditförluster. Syfte: Syftet med studien är att undersöka vilken effekt IFRS 9 har på svenska banker efter införandet. Studien undersöker även om effekten varierar beroende av bankers storlek. Metod: För att uppnå studiens syfte har en kvantitativ studie med deduktiv ansats tillämpats. Sekundärdata har inhämtats ur bankernas årsredovisningar för 2018 från respektive hemsida. Banker som ingår
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Jacobson, Josefin, and Maja Wramberg. "IFRS 9 och dess påverkan på bankers finansiella ställning : En kvantitativ studie om redovisningsstandardens påverkan på noterade banker inom EU." Thesis, Södertörns högskola, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-44500.

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Bakgrund och problemformulering: Den 1 januari 2018 infördesredovisningsstandarden IFRS 9 för finansiella instrument, vilken ersätter den tidigare kontroversiella standarden IAS 39. Den nya standarden innehåller bland annat en kreditförlustmodell som innebär att inte bara inträffade utan även förväntadek reditförluster ska redovisas, vilket skiljer sig från den tidigare kreditförlustmodellen där endast konstaterade förluster redovisades. Banker ansågs vara den typ av företagsom skulle komma att bli särskilt påverkade av den nya kreditförlustmodellen som IFRS 9 innebär. Bortsett från redovisnin
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Klefvenberg, Louise, and Viktoria Nordlander. "IFRS 9 replacing IAS 39 : A study about how the implementation of the Expected Credit Loss Model in IFRS 9 i beleived to impact comparability in accounting." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-260320.

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This thesis examines how the implementation process of Expected Credit Loss Model in the accounting standard IFRS 9 – Financial instruments is perceived and interpreted and how these factors can affect comparability in accounting. One of the main changes with IFRS 9 is that companies need to account for expected credit losses rather than just incurred ones. The data is primarily collected through a web survey where all of Nordic banks and credit institutes with a minimum book value of total assets of euro 1 billion, are invited to participate. The presentation of the collected data from the we
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Lopes, Maria Leonor Grossinho Fontinha Jacinto. "Loss given default : a backtesting exercise." Master's thesis, Instituto Superior de Economia e Gestão, 2018. http://hdl.handle.net/10400.5/18107.

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Mestrado em Mathematical Finance<br>After January 2018, the new accounting standard IFRS 9 Financial Instruments was mandatory practice for all Financial Institutions. Introducing the new impairment model, which focus on expected credit losses (ECL) instead of incurred losses established previous in IAS 39 Measurement and Recognition. According to the new standard, the risk parameters involved in the computation of the ECL are required to be periodically revised. The Loss Given Default (LGD) is a risk input which represents the loss in case of a financial instrument defaults. Hence, the aim
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Eriksson, Neil, and Niklas Rådström. "The implications of IFRS 9 – for Equity Analysts." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-389363.

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The financial crisis of 2008 highlighted problems with the accounting standard IAS 39, with claims of high complexity, introduction of procyclicality in the financial statements and a proposed role of contributing to the financial crisis. The International Accounting Standard Board issued the predecessor, IFRS 9, which became effective on January 1st, 2018. IFRS 9 introduces a forward-looking Expected Credit Loss model, which significantly change the accounting of loss provisions. With the objective to provide high accounting quality, the International Accounting Standard Board and Financial A
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Pazzoto, Bruno Bortoluzzo. "Modelagem da perda esperada: uma alternativa para tratar o efeito da correlação entre a PD e LGD." reponame:Repositório Institucional do FGV, 2012. http://hdl.handle.net/10438/10073.

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Submitted by Bruno Bortoluzzo Pazzoto (brunopazzoto@hotmail.com) on 2012-10-01T13:52:54Z No. of bitstreams: 1 dissertacao bruno pazzoto - versão final.pdf: 1116879 bytes, checksum: 97b2413340bda7342a4871944c193ff1 (MD5)<br>Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2012-10-01T14:37:42Z (GMT) No. of bitstreams: 1 dissertacao bruno pazzoto - versão final.pdf: 1116879 bytes, checksum: 97b2413340bda7342a4871944c193ff1 (MD5)<br>Made available in DSpace on 2012-10-01T15:10:54Z (GMT). No. of bitstreams: 1 dissertacao bruno pazzoto - versão final.pdf:
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Pereira, Bernardo Vieira Gonçalves. "Estudo sobre evolução do balanço de um banco em situação de stress económico : modelo macroeconómico de PD." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19770.

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Mestrado em Econometria Aplicada e Previsão<br>Este relatório de estágio enquadra-se no âmbito do Trabalho Final de Mestrado para o Mestrado de Econometria Aplicada e Previsão do Instituto Superior de Economia e Gestão (ISEG). O estágio decorreu na Deloitte Consultores, S.A., num dos escritórios de Lisboa, com o intuito de me preparar para a realidade do mercado de trabalho através de um processo de integração na empresa durante a realização das atividades propostas. Neste relatório pretende-se expor um retrato daquilo que foram os meus primeiros seis meses de trabalho na Deloitte, através d
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Books on the topic "Expected Credit Loss"

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Gross, Marco, Dimitrios Laliotis, Mindaugas Leika, and Pavel Lukyantsau. Expected Credit Loss Modeling from a Top-Down Stress Testing Perspective. International Monetary Fund, 2020.

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Gross, Marco, Dimitrios Laliotis, Mindaugas Leika, and Pavel Lukyantsau. Expected Credit Loss Modeling from a Top-Down Stress Testing Perspective. International Monetary Fund, 2020.

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Gross, Marco, Dimitrios Laliotis, Mindaugas Leika, and Pavel Lukyantsau. Expected Credit Loss Modeling from a Top-Down Stress Testing Perspective. International Monetary Fund, 2020.

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Simon, Gleeson. Part II Commercial Banking, 7 Credit Risk. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198793410.003.0007.

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This chapter discusses the concept of credit risk. Of all the risks that banks are exposed to, credit risk is the most important and the most intuitively obvious. It is important to remember that credit means more than simply loans. At the heart of financial transactions are credit exposures. For an economist, the function of a bank is maturity transformation and intertemporal transfers of resources. But in a world where debts were always repaid, these functions would be as mechanical as the transmission of water or electricity. It is the unpredictability of credit that differentiates banking
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Torluccio, Giuseppe, Paolo Palliola, Paola Brighi, et al. IFRS9 e le sfide di contesto. AIFIRM, 2021. http://dx.doi.org/10.47473/2016ppa00032.

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Under IFRS9, Financial Institutions are required to implement impairment frameworks to determine the expected losses on their credit portfolio taking into account the current (so called “point in time”) and the prospective (so called “forward looking”) economic cycle. The Covid-19 pandemic, which began in early 2020, has posed significant challenges for Financial Institutions in their ability to manage credit risk. Despite numerous guidelines given by regulators, estimating IFRS9 expected loss continues to be a considerable challenge. The challenge partly stems from the relationship between ma
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Simon, Gleeson. Part II Commercial Banking, 9 Model-Based Approaches to Risk Weighting. Oxford University Press, 2018. http://dx.doi.org/10.1093/law/9780198793410.003.0009.

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This chapter discusses the Basel risk model. Every financial institution expects to suffer some level of default. Consequently, all properly run banks make provisions for some level of default on their existing assets. This is known as expected loss. At some points losses will be lower than those expected, and at some points they will be higher. The task of the regulator is to set a capital requirement which just skims the top of the actual loss experience curve. If the capital requirement is set significantly higher than this, then banks will be penalized by being required to hold excessive c
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Book chapters on the topic "Expected Credit Loss"

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Lamaj, Merjona. "IFRS 9 and the Expected Credit Loss Model." In The Effect of Covid-19 on Loan Loss Provisions and Earnings Management of European Banks. Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-40060-6_2.

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Mohammadali-Haji, Ahmed, Karabo Sihiya, and Kyle Triegaardt. "Expected Credit Loss Provision Practices in South Africa: An Analysis of the Decision Usefulness of the Forward-Looking Disclosures." In Springer Proceedings in Business and Economics. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-84885-8_45.

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"Base Expected Loss and Base Correlation Smile." In The Art of Credit Derivatives. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119206620.ch11.

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"Consistency across Capital Structure and Maturities: Expected Tranche Loss." In Credit Models and the Crisis. John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781118374733.ch5.

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Bellini, Tiziano. "Introduction to Expected Credit Loss Modelling and Validation." In IFRS 9 and CECL Credit Risk Modelling and Validation. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-814940-9.00009-8.

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Bart PM, Joosen. "Part III Quantitative Capital Requirements, 6 The Definition of Default, Loss Distribution, Expected and Unexpected Loss, and Provisioning in the Context of Credit Risk." In Capital and Liquidity Requirements for European Banks. Oxford University Press, 2022. http://dx.doi.org/10.1093/law/9780198867319.003.0006.

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This chapter evaluates the principles for assessing credit risk, the consequences this has for capital requirements, and the fundamental approach that is chosen for all banks in this area. Absorbing losses is one of the functions of bank capital. As regards the credit risk concerning the bank’s exposures, it can generally be argued that banks will suffer losses on their credit portfolios due to counterparties failing to pay interest, the principal or costs incurred by the bank and attributable to the relevant loans. Banks will by nature always be faced with such losses, the only question of wh
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Anderson, Raymond. "Finance." In The Credit Scoring Toolkit. Oxford University PressOxford, 2007. http://dx.doi.org/10.1093/oso/9780199226405.003.0026.

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Abstract Ultimately, lenders’ main goal is to make a profit, whether by increasing revenue, decreasing expenses, or both. Thus far, very little has been mentioned about these key dynamics. This module’s final chapter takes a side step, to look at key subject areas directly related to finance: In the credit environment, provisions are raised for expected loan losses. They are a key part of prudent credit risk management; even the earliest moneylenders grappled with the problem mentally, but did not have the proper tools until after modern accounting was developed in the fifteenth century. Altho
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Bandyopadhyay, Arindam. "Matrix Algebra and their Application in Risk Prediction and Risk Monitoring." In Basic Statistics for Risk Management in Banks and Financial Institutions. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192849014.003.0005.

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Matrix Algebra concept and its numerous application in the measurement of credit risk as well as market risk have been elaborated in this chapter. A matrix is a rectangular array of elements. The transition matrix derived from the concept of matrix algebra has numerous applications in predicting bond valuation, value at risk analysis, and loan portfolio monitoring. The Markov chain process is used by reputed rating agencies and also the best practiced banks to predict probabilities of rating migration including analysis of default risk. It also enables a bank to estimate PD for different horiz
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Cleary, Timothy, and Charles H. R. Morris. "Regulatory Capital Implications of Achieving Significant Risk Transfer." In Credit Risk Mitigation and Synthetic Securitization. Oxford University Press, 2025. https://doi.org/10.1093/law/9780198891062.003.0011.

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Abstract This chapter examines how achieving significant risk transfer (SRT) affects regulatory capital and risk-weighted assets for both traditional and synthetic securitizations. It explains how SRT enables originators to derecognize securitized exposures under Articles 244, 245, and 251 of the CRR, reducing risk-weighted exposure amounts and altering expected loss calculations. The chapter explores the methodologies for calculating securitization tranche risk weights—the SEC-IRBA, SEC-SA, and SEC-ERBA—as well as the non-neutrality principle which underpins the securitization framework. The
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Smith, J. M. W. "Information and Notices." In The Law of Consumer Credit and Hire. Oxford University PressOxford, 2009. http://dx.doi.org/10.1093/oso/9780199230365.003.0009.

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Abstract Once a regulated consumer credit agreement or a regulated consumer hire agreement has been made, the creditor or owner is required to provide periodic statements, information and copy documents on request, and notices when the debtor or hirer is in default. The requirements, as expanded by the Consumer Credit Act (CCA) 2006 with effect on and from 1 October 2008, are detailed but not always clear. Questions arise, for example, as to who is the ‘creditor’, what is a ‘copy’ of a document, what is meant by a rate of interest ‘applicable on a per annum basis’, when a debtor ‘ceases to be
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Conference papers on the topic "Expected Credit Loss"

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Prasetya, Rivan, and Rofikoh Rokhim. "Analysis of Bond’s IFRS 9 Expected Credit Loss using Vasicek Method." In Proceedings of the 4th International Conference on Economics, Business and Economic Education Science, ICE-BEES 2021, 27-28 July 2021, Semarang, Indonesia. EAI, 2022. http://dx.doi.org/10.4108/eai.27-7-2021.2316899.

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Morshed, Amer Qasem Abdallah. "APPLYING THE EXPECTED CREDIT LOSS MODEL UNDER IFRS 9 ON ISLAMIC SUKUK: EMPIRICAL EVIDENCE FROM JORDAN PUBLICLY TRADED COMPANIES." In 15th International Bata Conference for Ph.D. Students and Young Researchers. Tomas Bata University in Zlín, 2019. http://dx.doi.org/10.7441/dokbat.2019.076.

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Garud, Y. S., and David A. Steininger. "A Rational Basis for Deterministic Margins in CUF-Based Fatigue Evaluation With Uncertainty." In ASME 2015 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/pvp2015-45806.

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One of the aging issues of concern in the light-water reactor power plants is the fatigue degradation due to cyclic loads for which the updated regulatory guidelines have factored in the water environment effects that were not in the original design basis analyses. These guidelines are also applicable to newer plant designs not yet in operation. In both these cases, notably, the design/analysis is deterministic with several factors conservatively used as an engineering judgment to address various sources of uncertainty in the cumulative usage factor (CUF) based fatigue evaluation. The use of d
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Crivellari, Anna, Alessandro Tugnoli, Costanza Martina, Sarah Bonvicini, and Valerio Cozzani. "Inherently Safer Choices in Early Design of Offshore Oil and Gas Installations: A Multi-Target KPI Approach." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77700.

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As offshore oil &amp; gas activities are currently evolving towards more productive yet complex situations, the availability of efficient safety metrics has become essential in the early stages of offshore oil &amp; gas projects to underline potential major accidents hazards and clearly communicate safety criticalities. Inherent safety has demonstrated to be a widespread concept in offshore risk management strategies, but there are few preliminary studies in the existing literature about systemic indexing to orient the conceptual and basic design stages of the project lifecycle. In the present
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Mensorale, Opeoluwa, and Victor Odumuyiwa. "Borrowers' Loan Repayment Coefficient Prediction Using Machine Learning." In International Conference on Artificial Intelligence and Robotics. Machine Intelligence Research Group (MIRG), 2023. https://doi.org/10.52968/15064183.

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Nano loan and unsecured loans is a fast-growing trend in the Nigeria fintech space. User creditworthiness and loan default is a problem for the whole industry. Traditional credit scoring methods have limitations in assessing the creditworthiness of diverse applicants by Loan Credit officers. In most cases, businesses lose money due to high defaults in customer loans on their loan investment portfolios. The loan repayment coefficient is a measurement of how soon a user is likely to repay a loan based on the user's historical data or similar users in the same demographic data historical data. Th
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Urazov, Aibek, and Iliyas Zholshybekuly. "Integrated Production Schedule." In SPE Caspian Technical Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/217584-ms.

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Abstract The focus of this comprehensive study is the mitigation and prevention of incidents that may lead to potential production loss (LPO) at the Tengiz and Korolev fields, two vital components of the oil and gas industry. These fields confront numerous challenges in production and ongoing operational activities. The primary objective of this research is the development and implementation of an integrated production schedule (IPS) in conjunction with a reservoir simulation model to foresee field production performances and proactively manage production operations. The core of this process r
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Reports on the topic "Expected Credit Loss"

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Dejuan-Bitria, Daniel, Wayne R. Landsman, Sergio Mayordomo, and Irene Roibás. How do changes in financial reporting standards affect relationship lending? Banco de España, 2024. http://dx.doi.org/10.53479/37892.

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This paper analyses the effect of the expected credit loss model under IFRS 9 on relationship lending in Spain. We document that relationship exclusivity between a bank and a firm has a positive effect on the growth of credit. However, this positive effect is significantly reduced after implementation of IFRS 9. We estimate that in 2018 the negative impact of IFRS 9 on relationship lending led to a reduction in credit to Spanish non-financial firms of 2.8% of their total outstanding credit, suggesting a sizeable effect on the availability of credit. For borrowers with Stage 1 loans, we show th
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2

Financial Stability Report - Second Semester of 2020. Banco de la República de Colombia, 2021. http://dx.doi.org/10.32468/rept-estab-fin.sem2.eng-2020.

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The Colombian financial system has not suffered major structural disruptions during these months of deep economic contraction and has continued to carry out its basic functions as usual, thus facilitating the economy's response to extreme conditions. This is the result of the soundness of financial institutions at the beginning of the crisis, which was reflected in high liquidity and capital adequacy indicators as well as in the timely response of various authorities. Banco de la República lowered its policy interest rates 250 points to 1.75%, the lowest level since the creation of the new ind
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3

Financial Stability Report - September 2015. Banco de la República, 2021. http://dx.doi.org/10.32468/rept-estab-fin.sem2.eng-2015.

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From this edition, the Financial Stability Report will have fewer pages with some changes in its structure. The purpose of this change is to present the most relevant facts of the financial system and their implications on the financial stability. This allows displaying the analysis more concisely and clearly, as it will focus on describing the evolution of the variables that have the greatest impact on the performance of the financial system, for estimating then the effect of a possible materialization of these risks on the financial health of the institutions. The changing dynamics of the ri
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4

Monetary Policy Report, April 2024. Banco de la República, 2024. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr2-2024.

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Inflation continues to fall, but it is above the 3% target, and it is projected to continue falling until it reaches it in 2025. Economic growth is low, but it would recover, and by 2025, economic activity would reach a path that can be sustained over time without causing unwanted changes in inflation, employment, or the external balance. The current monetary policy interest rate is compatible with the convergence of inflation to the target in 2025 and with the recovery of economic growth in the next two years. • Annual inflation has been decreasing for a year and is projected to continue, wit
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