Expected Credit Loss Research Articles

Bank audit committee financial expertise and timely loan loss recognition

AbstractThis study investigates the effects of audit committee financial expertise on the timeliness of banks' loan loss provisions. I employ two regulatory shocks that mandated audit committee expertise—the Federal Deposit Insurance Corporation Improvement Act in 1991 (FDICIA) and a modified listing standard for NYSE and NASDAQ firms in 1999—as quasi‐exogenous settings to investigate the effects of audit committee financial expertise on the timeliness of loan loss provisioning. Using a difference‐in‐differences research design, I find that the timeliness of loan loss provisions increases with audit committee financial expertise both for the FDICIA treatment group, which had larger banks than the control group, and for the NYSE and NASDAQ exchange treatment group, which had smaller banks than the control group. Further, I find that the results are stronger for banks that have lower regulatory scrutiny, are audited by Big 4 auditors, and do not have staggered boards. Finally, I find that audit committee financial expertise decreases discretionary loan loss provisions and financial restatements. Overall, these findings suggest the importance of audit committee financial expertise in loan‐related matters, which is particularly relevant in the context of the recent Current Expected Credit Losses implementation.

Higher Education Institutions’ Credit Loss Recognition

The current expected credit loss (CECL) accounting guidance represents a forward-looking methodology for determining credit loss provisions by private colleges and universities’ lending activities beginning with fiscal year 2023-2024. The discussion presents information regarding the types and amounts of lending activities private colleges and universities engage in and the rationale of their lending programs. Provisions of the accounting guidance together implementation decisions, processes, and disclosures are part of the review. The study concludes with the accounting guidance’s impact on higher education fiscal decision making, financial reporting, and the ramifications of the guidance to provide useful information to both higher education management and financial statement users.

The Effect of the Current Expected Credit Loss Approach on Banks’ Lending during Stress Periods: Evidence from the COVID-19 Recession

ABSTRACT In the wake of the financial crisis, policymakers expressed the concern that the incurred loss model delays loan loss recognition to economic stress periods and thereby exacerbates banks’ lending contraction during these periods. Addressing this concern, the FASB issued Accounting Standards Update 2016-13, which requires large public banks to accrue for loan losses using the current expected credit loss (CECL) approach starting in January 2020. We hypothesize and find that banks that adopted CECL prior to the COVID-19 pandemic increased loan loss provisions and reduced loan growth during the accompanying recession more than other banks. The lending contraction is stronger for adopting banks with low regulatory capital and low loan impairment and is primarily driven by commercial loans. Lastly, we find that counties in which CECL-adopting banks have higher market share experience larger increases in unemployment rates during the recession and slower subsequent recoveries. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: E32; G21; G28; M41; M48.

Impact of IFRS 9 Implementation and Audit Committee Effectiveness on Earnings Management in The Indonesian Banking Sector

Background- The implementation of IFRS 9, utilizing the Expected Credit Loss (ECL) method, along with effective oversight from the audit committee, can be a relevant strategy to anticipate earnings management practices. Purpose- to examine the impact of IFRS 9 implementation and audit committee supervision on restricting managerial discretion in loan loss provisions. Design/methodology/approach- This study will use a quantitative analysis method using secondary data from an annual report. The sampling method used in this study was purposive sampling, which resulted in selecting 42 banks listed on the Indonesian Stock Exchange from 2017 to 2022. This study uses the data panel analysis method with the STATA analysis tool. Findings- This research found that the implementation of IFRS 9 and audit committees had an impact on increasing bank managerial discretion. This explains that the implementation of IFRS 9 and the audit committee have not been able to limit managerial discretion, which may be due to the influence of unstable economic conditions due to the pandemic and countercyclical policy to anticipate the impact of the pandemic. Research limitation- The potential impact of the COVID-19 pandemic on research outcomes related to managerial discretion and the effectiveness of audit committee oversight. Originality/Value- To enhance the literature related to the trends of the impact of PSAK implementation in Indonesia on earnings management more comprehensively by extending the research period and contributing to the literature by employing multiple criteria to identify the quality of oversight provided by the audit committee.

How Does Loan Loss Accounting Influence Bank Lending? Evidence from the Current Expected Credit Loss (CECL) Model

How Does Loan Loss Accounting Influence Bank Lending? Evidence from the Current Expected Credit Loss (CECL) Model

The Effect of Credit Risk Management on the Financial Performance of Banks Listed on the IDX

This study aims to analyze the influence of credit risks such as non-performing loans (NPL), expected credit loss provision (ECL), and loan-to-deposit ratio (LDR) on the bank's financial performance as measured by the return on assets (ROA). This study uses purposive sampling as a sampling method. The sample taken is a conventional commercial bank company listed on the Indonesia Stock Exchange (IDX) for a five-year period from 2018 – 2022. Data were collected from 44 banks and analyzed using descriptive statistics and fixed-effect models for hypothesis testing. Data testing was carried out by panel data regression analysis method using E-views 9.0. The results of this study show that (1) NPL has a negative effect on ROA. An increase in NPLs will lower ROA, and vice versa. (2) ECL has a negative effect on ROA. An increase in ECL will lower ROA, and vice versa. (3) LDR has no effect on ROA. Banks need to maintain low NPLs and ECLs to maximize the bank's financial performance. Based on this research, banks are advised to conduct a careful credit evaluation before a loan application is approved. The researcher recommends that further research can add other independent variables that affect the financial performance of banks in order to get more accurate and general results.

The Effect of the Current Expected Credit Loss Model on Conditional Conservatism of Banks and Its Spillover Effect on Borrower Conservatism

The Effect of the Current Expected Credit Loss Model on Conditional Conservatism of Banks and Its Spillover Effect on Borrower Conservatism

Stress Test of BPRS and BUS Capital for the 2014-2022 Period Using the ECL Approach

The operation of BUS and BPRS cannot be separated from the risks experienced, one of which is capital risk. The capital stress test used to calculate the capital adequacy of BUS and BPRS is the calculation of Expected Credit Loss (expected loan loss). ECL is the result of multiplying PD, LGD, and EAD. This study aims to determine the assessment and differences in capital stress tests using the ECL approach in BUS and BPRS. This research uses a descriptive quantitative approach. The method used is purposive sampling. The samples of this study were 12 BUS and 3 BPRS. The data used is secondary data in the form of annual financial reports taken from the official websites of BUS and BPRS for 2014-2022. The results of this study indicate that the assessment of the capital stress test using the ECL approach on BUS is classified as stage 1 (performing), and BPRS is classified as stage 2 (under-performing). A significant difference was found between BUS and BPRS.

Expected credit losses in international banking business

Expected credit losses in international banking business

The Impact of IFRS 9 Adoption on the Financial Performance and Sustainability of Romanian Credit Institutions

ABSTRACT This paper aims to quantify the impact of the policies established by IFRS (International Financial Reporting Standards) 9 regarding the recognition and measurement of financial instruments and derivatives on the sustainability and financial performance of Romanian credit institutions. The results show a positive significant impact on performance when the evaluation is made at fair value through profit and loss and a negative one when is made through elements of other comprehensive income. While the expected credit loss policy is essential to underpin prudential policy, it also brought some financial instability for the sampled institutions.

Effects of Expected Credit Losses on Credit Risk Management in Commercial Banks in East Africa

Effects of Expected Credit Losses on Credit Risk Management in Commercial Banks in East Africa

Expected credit loss modeling

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 banking organizations to comply with international standards, such as International Financial Reporting Standards (IFRS 9) and the Agreement on Banking Supervision and Capital (Basel 3). These standards define credit risk assessment requirements and capital requirements. Adherence to these standards is important not only for ensuring the stability and reliability of the financial system, but also for maintaining the trust of clients and investors. Compliance with international standards also makes banks competitive in the global market and promotes investment inflows and the development of the financial sector.IFRS 9 can be presented in various mathematical models. The article proposes an approach to choosing the appropriate model for forecasting the probability of default. The described model selection method allows banks to choose the optimal default forecast assessment model within the framework of the given standard. This contributes to a more accurate and reliable assessment of credit risk, in accordance with regulatory requirements, which will provide banks with the means for better forecasting and management of financial resources, as well as risk reduction.The model selection methodology saves a significant amount of time and resources, since the search for the optimal model occurs automatically. This allows us to react more quickly to changes in the economic environment, improve decision-making strategies and manage credit risks, which is of great importance for financial institutions in a competitive environment.There is currently a war going on in Ukraine, and forecasting using current methods becomes a difficult task due to unpredictable stressful situations for the economy. In such conditions, standard models may not be sufficiently adapted to account for increased risk and volatility. The proposed approach allows finding more conservative forecasting models that can be useful in unstable periods and war.

Impacts of the Transition to the Expected Loss Model on the Portuguese Banking Sector

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 Allowances (LLA) in loans, own equity, and the Common Equity Tier 1 (CET1) ratio across 13 Portuguese commercial banks. A mean comparison test is used to evaluate scenarios before and after the application of the ECL model, highlighting the importance of regulator actions and the adequacy of loss recognition policies, including the effects of European Union. The results obtained demonstrate significant negative impacts on the net values of loans, own equity, and the CET1 ratio upon adopting the IFRS 9 ECL model due to the widespread increase in LLAs.

Impacts of the Expected Credit Loss Model on Pro-Cyclicality, Earnings Management, and Equity Management in the Portuguese Banking Sector

This article delves into the pro-cyclicality of loan loss provisions (LLPs) and earnings management, along with equity management, in Portuguese banks against the backdrop of implementing the IFRS 9’s expected credit loss (ECL) model. It concentrates on how LLPs mirror economic cycles and financial management practices, providing valuable insights into the operational dynamics of the Portuguese banking sector, marked by distinct economic and regulatory challenges. The research examined a sample of five Portuguese commercial banks, chosen from a group of seventeen in the Portuguese Banking Association. Data spanning from 2013 to 2022 were manually gathered. A multiple linear regression model was employed to scrutinize the relationship between LLPs and variables indicative of economic cycles and the earnings and equity management. The methodology use was a multiple linear regression model. The analysis indicates a pro-cyclicality in LLPs within the Portuguese context, with a positive response of LLPs to economic indicators like unemployment. Contrarily, the extent of earnings and equity management under the ECL model was less marked compared to the incurred credit loss (ICL) model, suggesting the impact of more stringent regulatory measures. The research corroborates the pro-cyclicality of LLPs in Portuguese banks under the ECL framework, underscoring the necessity for ongoing monitoring and refinement of models for forecasting and recognizing credit losses. The findings point to an area for improvement in financial management practices, despite regulatory enhancements, to promote transparency and ensure financial stability.

Probability of default for lifetime credit loss for IFRS 9 using machine learning competing risks survival analysis models

This study introduces a machine learning competing risks survival analysis model aiming at exploring the Probability of Default component of credit risk. Due to modeling of a cumulative probability of default over time, the model is applicable to assess Lifetime Expected Credit Loss under the International Financial Reporting Standard (IFRS) 9 regulation for financial institutions. Whilst most credit models focus on the default event itself, in many loan transactions, there is a competing event affecting risk: the possibility of the borrower prepay their debt before maturity. In this case, credit risk ceases to exist. We derive a statistical model that supports handling competing risks (credit risk and prepayment risk) in a machine learning survival analysis setup. As there is no available implemented computer package or library, we build the computational algorithm with subdistribution hazards using boosting as an ensemble method and componentwise least square models as base learners. Results of the model are generated using a dataset of credit card refinancing operations of a US financial institution. We observe, comparing different survival analysis techniques, that ComponentWise Gradient Boosting (CWGB) models showed competetive performance on both scenarios (subdistribution hazards and cause-specific models) compared to benchmark models. The derived model is useful to address the guidelines of the IFRS 9 for credit risk, taking into account the context of lifetime credit exposure.

Ethics in Financial Reporting Methods: The Case of Vontsira, Inc.

ABSTRACT This case allows students to wrestle with the ethical decisions relating to accounting choices. At issue in this case is the timing of the implementation of the Current Expected Credit Losses (CECL) model standard. The objectives of the case are to help students (1) raise their awareness of the ethical decisions inherent to accounting choices, (2) weigh the validity of different viewpoints and approaches, (3) understand the far-reaching implications of ethical decisions in financial reporting, and (4) practice preparing to effectively advocate their positions in a professional setting. When delivered alongside lessons on accounting for receivables and doubtful accounts, the case can help reinforce the real implications of the judgment involved in estimating bad debt. It is also appropriate for any graduate or upper division undergraduate accounting course in which students discuss ethics and codes of conduct.

Constraints on provisioning at public versus private community banks

AbstractWe compare the responses of publicly held versus privately held community banks to the June 2016 issuance of the current expected credit loss (CECL) standard, which altered the way US banks provision for loan losses. We find that following issuance but before implementation, the relation between earnings and provisions strengthened among privately held banks but not among publicly held banks. This is consistent with US Securities and Exchange Commission regulation and market monitoring placing greater constraints on publicly held banks relative to privately held banks, preventing publicly held banks from moving toward the CECL standard early.

Investigating the applicability of the expected credit loss model to Islamic Sukuk: Law aspects

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 and accounting were interviewed for qualitative perceptions, while the data were supplemented by a survey of 182 stakeholders in the Islamic finance sector. The results tend to indicate that the ECL model is consistent with Sharia rules and substantially improves risk management under Islamic finance without adversely affecting Sharia compliance, especially in the case of Sukuk (Paltrinieri et al., 2023; Uluyol, 2021). However, the operational challenges of the non-interest-based nature and diverse structures of Sukuk obviously require customized approaches when applying the ECL model. This research is hence relevant and contributes valuable practical considerations to the literature for policymakers and practitioners in Islamic finance and accounting toward aligning Islamic financial products with international standards (Adelopo et al., 2023).

Variance Compression Bias in Expected Credit Loss Estimates Derived from Stress-Test Macroeconomic Scenarios

Variance Compression Bias in Expected Credit Loss Estimates Derived from Stress-Test Macroeconomic Scenarios

The impact of Current Expected Credit Loss Provision(CECL) on the information transmission of banks' Loan Loss Provision(LLP)

The impact of Current Expected Credit Loss Provision(CECL) on the information transmission of banks' Loan Loss Provision(LLP)