Credit Loss Model Research Articles

Experimental Evidence on the Impact of Replacing the Incurred Credit Loss Model of Bank Loan Loss Provisions with the International or US Accounting Standards Boards’ Expected Credit Loss Models

Our objective is to test-bed the new Expected Credit Loss (ECL) and Current Expected Credit Loss (CECL) models for bank credit loss accounting to identify the potential consequences of their implementation. In particular, whether and how ECL and CECL approaches could lead to divergence in credit loss accounting practices in the U.S. relative to the rest of the world is an unanswered question. To do this, we develop a stylized bank-loan setting in a controlled laboratory environment with eight different secured personal-loan portfolios. Fifty-six senior accounting students take the role of loan managers responsible for making annual loan-loss reserve decisions in a between-subjects design under the rules of either the ECL or CECL models. We examine the effects of mandating the ECL or CECL model in terms of their impacts on the adequacy of loan-loss reserves, the comparability and predictability of loan-loss reserves and the volatility of reported profit.

МЕТОДИКА ОЦЕНКИ ОЖИДАЕМЫХ КРЕДИТНЫХ УБЫТКОВ КАК ИНСТРУМЕНТ УПРАВЛЕНИЯ РИСКАМИ НЕКРЕДИТНЫХ ФИНАНСОВЫХ ОРГАНИЗАЦИЙ

The article analyzes the use of IFRS 9 for credit risk management of non-credit financial institutions. In 2018, the new standard was applied for the first time in Russia, however, major market players – insurance companies and non-state pension funds – will only make the transition in 2022. This allows us to conclude that the study of this sphere is highly relevant. The hypothesis of the study is that the model for expected credit losses calculation can be used as a risk management tool for non-banking financial institutions. The study systematizes information from various legal acts and analyzes the impact of IFRS 9 on the financial statements of banks that have already begun to apply this model. Owing to the results of the study, it has been concluded that IFRS 9 allows organizations not only to adequately disclose information about financial instruments, but also to integrate risk management into the organization’s accounting. Existing examples of the transition to the new standard of credit organizations and small representatives of non-credit financial organizations show the importance of the adequate application of the expected credit loss model, but do not allow us to entirely use their created internal documents due to the specifics of insurance companies and nonstate pension funds.

IASB's independence in the due process: an examination of interest groups’ influence on the development of IFRS 9

AbstractThis mixed‐method study examines whether and how the International Accounting Standards Board (IASB) was influenced by interest groups during the development of the expected credit loss (ECL) model for IFRS 9 Financial Instruments. Content analysis of 327 comment letters revealed that the IASB was influenced. However, Fisher's exact test and chi‐square goodness‐of‐fit test showed that, to a greater extent, the influence was not significant. Furthermore, qualitative analyses of the arguments put forward by interest groups showed that as a result of interest groups’ inputs, accounting requirements for the ECL model were made more operational, less complex and potentially productive of more comparable financial information.

EXPECTED CREDIT LOSS MODEL BY IFRS 9 AND ITS POSSIBLE EARLY IMPACTS ON EUROPEAN AND TURKISH BANKING SECTOR

ABSTRACT IFRS 9 – ²Financial Instruments², the replacement of IAS 39 – ²Financial Instruments: Recognition and Measurement² was issued by International Accounting Standards Board in July, 2014 and became mandatory on January 1, 2018. The significant change implemented in the new standard is about the “impairment” phase which is based on "Expected Credit Losses" (ECL) rather than "Incurred Credit Losses". In this study, the measurement and recognition of allowances for impairment are explained and then the expected possible qualitative and quantitative effects of this transition primarily in the European Banking Industry are analyzed and compared with Turkish Banking Industry. It is expected that, ECL application by European banks would result in on average 13%-18% increase in loss provisions and Common Equity Tier 1 (CET1) and total capital ratio decrease by on average 45-75 basis points (bps) and 35-50 bps, respectively whereas the total amount of provisions will be diminishing by 4.1% and will have 33 bps and 21 bps positive impacts on CET1 and total capital adequacy ratio on average, respectively for Turkish banks.

Testing the Efficacy of Replacing the Incurred Credit Loss Model with the Expected Credit Loss Model

We use a controlled laboratory environment to provide evidence on the potential efficacy of the replacement of the Incurred Credit Loss (ICL) Model of International Accounting Standard (IAS 39) by the Expected Credit Loss (ECL) model of IFRS 9 to account for credit impairment losses. We focus on the simplified version of the ECL model using an uncertain production environment as the context. We induce incentives consistent with the existing rigid rule-based ICL model and the proposed forward-looking principle-based ECL model. Our primary finding is that the combined effects of eliminating the minimum ‘probable’ threshold condition together with allowing managers to incorporate forward-looking information increase both the amount and adequacy of periodic reserve decisions. In addition, we analyze the effects of increased flexibility under the new credit-loss model on earnings management using three different compensation schemes. We find that while the replacement of the ICL model with the ECL model facilitates higher reserves, the resulting increased earnings management varies across compensation schemes, is less than predicted, and does not offset the potential of the ECL model’s positive effects. The results provide ex ante evidence on the likely intended and unintended consequences of implementing the ECL model.

Practical Issues in the Current Expected Credit Loss (CECL) Model: Effective Loan Life and Forward-Looking Information

Practical Issues in the Current Expected Credit Loss (CECL) Model: Effective Loan Life and Forward-Looking Information

Test-Bedding the Replacement of the Incurred Credit Loss Model with an Expected Credit Loss Model: The Case of Trade Receivables

We use a laboratory-controlled environment to provide experimental evidence on the potential intended and unintended consequences of the mandatory replacement of the Incurred Credit Loss Model (ICL) of IAS 39 by the Expected Credit Loss Model (ECL) of IFRS 9. We focus on the simplified version of the ECL model using the case of allowances for trade-receivable losses as the context. In particular, we induce incentives consistent with the existing backward-looking rule-based ICL model and the proposed forward-looking ECL model. We find that eliminating the minimum “probable” threshold condition combined with allowing managers to use forward-looking information significantly improve the adequacy of credit loss allowances and their recognition in a more timely manner. This leads to higher profits over the economic cycle compared to an environment characterized by the ICL model. However, compensation incentives lead to higher levels of earnings management and dampening profits relative to the baseline case that maximizes the profits over the economic cycle. Taken together, we interpret our findings to indicate that while the replacement of the ICL model with the ECL model has the potential to mitigate the severity of the adverse effects of the ICL model, it could entail unintended consequences for earnings management. With this new ECL model still in the pre-implementation stage, our results provide ex-ante evidence to policymakers on the advantages of the ECL model as well as about the unintended outcomes provided by its inherent incentives.

The Interaction of the IFRS 9 Expected Loss Approach with Supervisory Rules and Implications for Financial Stability

This paper examines the interaction of the International Financial Reporting Standard (IFRS) 9 expected credit loss (ECL) model with supervisory rules and discusses potential implications for financial stability in the European Union. Compared to the incurred loss approach of IAS 39, the IFRS 9 ECL model incorporates earlier and larger impairment allowances and is more closely aligned with regulatory expected loss. The earlier recognition of credit losses will reduce the build-up of loss overhangs and the overstatement of regulatory capital. In addition, extended disclosure requirements are likely to contribute to more effective market discipline. Through these channels IFRS 9 might enhance financial stability. However, due to the reliance on point-in-time estimates of the main input parameters (probability of default and loss given default) IFRS 9 ECLs will increase the volatility of regulatory capital for some banks. Furthermore, the ECL model provides significant room for managerial discretion. Bank supervisors might play an important role in the implementation of IFRS 9, but too much supervisory intervention bears the risk of introducing a prudential bias into loan loss accounting that compromises the integrity of financial reporting. Overall, the potential benefits of the standard will crucially depend on its proper and consistent application across jurisdictions.

Haar wavelets-based approach for quantifying credit portfolio losses

This paper proposes a new methodology to compute Value at Risk (VaR) for quantifying losses in credit portfolios. We approximate the cumulative distribution of the loss function by a finite combination of Haar wavelet basis functions and calculate the coefficients of the approximation by inverting its Laplace transform. The Wavelet Approximation (WA) method is particularly suitable for non-smooth distributions, often arising in small or concentrated portfolios, when the hypothesis of the Basel II formulas are violated. To test the methodology we consider the Vasicek one-factor portfolio credit loss model as our model framework. WA is an accurate, robust and fast method, allowing the estimation of the VaR much more quickly than with a Monte Carlo (MC) method at the same level of accuracy and reliability.

Computation of risk contribution in the Vasicek portfolio credit loss model

AbstractFor the calculation of the VaR contribution in the Vasicek one‐factor portfolio credit loss model, two methods, namely the saddlepoint approximation and importance sampling, are very attractive in terms of accuracy, speed and robustness. We explore their connection with the Esscher transform. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Higher-order saddlepoint approximations in the Vasicek portfolio credit loss model

This paper utilizes the saddlepoint approximation as an efficient tool to estimate the portfolio credit loss distribution in the Vasicek model. Value-atrisk (VaR), the risk measure chosen in the Basel II Accord for the evaluation of capital requirement, can then be found by inverting the loss distribution. The VaR contribution (VaRC), expected shortfall (ES) and ES contribution (ESC) can all be calculated accurately. Saddlepoint approximation is well known to provide good approximations to very small tail probabilities, which makes it a very suitable technique in the context of portfolio credit loss. The portfolio credit model we employ is the Vasicek one-factor model, which has an analytical solution if the portfolio is well diversified. The Vasicek asymptotic formula fails, however, when the portfolio is dominated by a few loans much larger than the rest. We show that saddlepoint approximation is able to handle such exposure concentration. We also point out that the saddlepoint approximation technique can be readily applied to more general Bernoulli mixture models (possibly multi-factor). It can further handle portfolios with random loss given default (LGD).

Computation of VaR and VaR contribution in the Vasicek portfolio credit loss model: a comparative study

We compare various numerical methods for the estimation of the VaR and the marginal VaR contribution (VaRC) in the Vasicek one-factor portfolio credit loss model. The methods we investigate are the normal approximation, the saddlepoint approximation, a simplified saddlepoint approximation and importance sampling. We investigate each method in terms of speed, accuracy and robustness and in particular explore their abilities of dealing with exposure concentration.

Unbiased Capital Allocation in an Asymptotic Single Risk Factor (ASRF) Model of Credit Risk

This paper derives unbiased capital allocation rules for portfolios in which credit risk is driven by a single common factor and idiosyncratic risk is fully diversified. The methodology for setting unbiased capital allocations is developed in the context of the Black-ScholesMerton (BSM) equilibrium model. The methodology is extended to develop an unbiased capital allocation rule for the Gaussian ASRF structural model of credit risk. Unbiased capital allocations are shown to depend on yield to maturity as well as probability of default, loss given default, and asset correlations. Unbiased capital allocations are compared to capital allocations that are set equal to unexpected loss in a Gaussian credit loss model—an approach that is widely applied in the banking industry and used to set minimum bank regulatory capital standards under the Basel II Internal Ratings Based (IRB) approach. The analysis demonstrates that the Gaussian unexpected loss approach substantially undercapitalizes portfolio credit risk relative to an unbiased capital allocation rule. The results include a suggested correction for the IRB capital assignment function. The corrected capital rule calls for a substantial increase in minimum capital requirements over the existing Basel II IRB regulatory capital function.