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Article
Publication date: 1 April 2005

Henri Loubergé and Harris Schlesinger

This paper aims to propose a new method for credit risk allocation among economic agents.

Abstract

Purpose

This paper aims to propose a new method for credit risk allocation among economic agents.

Design/methodology/approach

The paper considers a pool of bank loans subject to a credit risk and develops a method for decomposing the credit risk into idiosyncratic and systematic components. The systematic component accounts for the aggregate statistical difference between credit defaults in a given period and the long‐run average of these defaults.

Findings

The paper shows how financial contracts might be redesigned to allow for banks to manage the idiosyncratic component for their own accounts, while allowing the systematic component to be handled separately. The systematic component can be retained, passed off to the capital markets, or shared with the borrower. In the latter case, the paper introduces a type of floating interest rate, in which the rate is set in arrears, based on a composite index for the systematic risk. This increases the efficiency of risk sharing between borrowers, lenders and the capital market.

Practical implications

The paper has several practical implications that are of value for financial engineers, loan market participants, financial regulators, and all economic agents concerned with credit risk. It could lead to a new class of structured notes being traded in the market.

Originality/value

The paper also illustrates the potential benefits of risk decomposition. Of course, as with any innovation, the implementation of the structured contracts would raise practical issues not addressed here. The paper also makes several simplifications: market risk is ignored; the level of default is constant and identical among borrowers. These simplifications could be lifted in future research on this theme.

Details

The Journal of Risk Finance, vol. 6 no. 2
Type: Research Article
ISSN: 1526-5943

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Book part
Publication date: 28 September 2020

Hongyi Chen, Jianghui Chen and Gaofeng Han

This chapter studies banksloan pricing behavior in mainland China during 2003–2013 by applying panel regressions to firm-level loan data and the estimated default

Abstract

This chapter studies banksloan pricing behavior in mainland China during 2003–2013 by applying panel regressions to firm-level loan data and the estimated default likelihood for listed companies. The authors find that with the progress of market-oriented financial reforms, banks generally require compensation for their exposure to borrowers’ default risks. It is even more so if the borrower is a non-state-owned enterprise (non-SOE), mainly due to the pricing behavior of the Big Four banks. Bank lending rates are shown to be less sensitive to the default risks of state-owned enterprises (SOEs). Our results also reveal that banks priced in firm default risks before 2008 financial crisis, but not necessarily so after the crisis. As for industries, we find that after the 2008 Global Financial Crisis, the real estate sector and other government-supported industries tended to enjoy better terms on loan pricing in terms of default risks. We believe the main reason is that the government stimulus policies tilted toward those industries that have played crucial roles in China’s economic growth.

Details

Emerging Market Finance: New Challenges and Opportunities
Type: Book
ISBN: 978-1-83982-058-8

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Article
Publication date: 26 July 2021

Shaun Shuxun Wang, Jing Rong Goh, Didier Sornette, He Wang and Esther Ying Yang

Many governments are taking measures in support of small and medium-sized enterprises (SMEs) to mitigate the economic impact of the COVID-19 outbreak. This paper presents…

Abstract

Purpose

Many governments are taking measures in support of small and medium-sized enterprises (SMEs) to mitigate the economic impact of the COVID-19 outbreak. This paper presents a theoretical model for evaluating various government measures, including insurance for bank loans, interest rate subsidy, bridge loans and relief of tax burdens.

Design/methodology/approach

This paper distinguishes a firm's intrinsic value and book value, where a firm can lose its intrinsic value when it encounters cash-flow crunch. Wang transform is applied to (1) calculating the appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs, (2) describing the frailty distribution for SMEs and (3) defining banks' underwriting capability and overlap index in risk selection.

Findings

Government support for SMEs can be in the form of an appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs.

Research limitations/implications

More available data on bank loans would have helped strengthen the empirical studies.

Practical implications

This paper makes policy recommendations of establishing policy-oriented banks or investment funds dedicated to supporting SMEs, developing risk indices for SMEs to facilitate refined risk underwriting, providing SMEs with long-term tax relief and early-stage equity-type investments.

Social implications

The model highlights the importance of providing bridge loans to SMEs during the COVID-19 disruption to prevent massive business closures.

Originality/value

This paper provides an analytical framework using Wang transform for analyzing the most effective form of government support for SMEs.

Details

China Finance Review International, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 10 July 2020

Azira Abdul Adzis, Hock Eam Lim, Siew Goh Yeok and Asish Saha

This study investigates factors contributing to residential mortgage loans default by utilizing a unique dataset of borrowers' default data from one of the pioneer lending…

Abstract

Purpose

This study investigates factors contributing to residential mortgage loans default by utilizing a unique dataset of borrowers' default data from one of the pioneer lending institutions in Malaysia that provides home financing to the public. Studies on mortgage loan default have been extensively examined, but limited studies utilize the individual borrower's data, as financial institutions generally hesitant to reveal their customers' data due to confidentiality issue.

Design/methodology/approach

This study uses logistic regression model to analyze 47,158 housing loan borrowers' data for the year 2016.

Findings

The findings suggest that male borrowers, Malay and other type of ethnicity, guarantor availability, loan original balance, loan tenure, loan interest rate and loan-to-value (LTV) ratio are the significant factors that influence mortgage loans default in Malaysia.

Research limitations/implications

Future studies may expand the sample by employing data from other types of financial institutions that would give greater insights as findings might vary due to differences in objectives, functions and regulations. In addition, the findings are subjected to the censoring bias where future studies could perform the survival analysis to control for censoring bias and re-validating the findings of the present study.

Practical implications

The findings provide valuable insights for lending institutions and the government to formulate housing loan policy in Malaysia.

Originality/value

To the best of the authors' knowledge, this is the first study in the context of emerging economies that uses financial institution's internal data to investigate factors of mortgage loan default.

Details

Review of Behavioral Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1940-5979

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Article
Publication date: 13 February 2017

Nevine Sobhy Abdel Megeid

This research aims to analyze and compare the effectiveness of liquidity risk management of Islamic and conventional banking in Egypt to ascertain which of the two banking

Abstract

Purpose

This research aims to analyze and compare the effectiveness of liquidity risk management of Islamic and conventional banking in Egypt to ascertain which of the two banking systems are performing better.

Design/methodology/approach

A sample of six conventional banks (CBs) and two Islamic banks (IBs) in Egypt was selected. Using the liquidity ratios, the investigation involves analyzing the financial statements for the period of 2004-2011. The data were obtained from Bank scope database.

Findings

The research found that in Egypt, CBs perform better in terms of liquidity risk management than IBs. The liquidity risk management significant differences between IBs and CBs could be attributed more cash availability to CBs than to IBs, in addition, Egyptian Central Bank regulations on capital and liquidity requirements for IBs disconcert IBs’ performance.

Practical implications

This research facilitates the bankers, academician, scholars and bankers to have an alluded picture about Egyptian banking developments in liquidity risk management. The results can be used by bankers’ policy decision-makers to improve and enhance their consideration for liquidity risk management.

Originality/value

This research covers a period and a country that compares CBs’ and IBs’ liquidity risk management. Its value is attributed to the increasing differentiation between CBs and IBs.

Details

Journal of Islamic Accounting and Business Research, vol. 8 no. 1
Type: Research Article
ISSN: 1759-0817

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Article
Publication date: 19 May 2014

Lorenzo Gai and Federica Ielasi

The purpose of this paper is to investigate the drivers influencing the risk of default on mutual guaranteed loans. The authors aim to verify whether default is influenced…

Abstract

Purpose

The purpose of this paper is to investigate the drivers influencing the risk of default on mutual guaranteed loans. The authors aim to verify whether default is influenced by the specific business policies of mutual guarantee institutions (MGIs) and to recommend guidelines for directing their operating management.

Design/methodology/approach

The authors analyse the guaranteed portfolios of 19 Italian MGIs and investigate the determinants of the defaulted positions at the end of June 2011. The sample consists of 167,777 guaranteed loans, of which 11,349 are in default. Using regression models, we identify the variables related to the business model of MGIs that are significantly associated with default on their positions.

Findings

The defaulted positions of MGIs are significantly correlated with the type of issued guarantees. This condition should be considered in defining product and price policies.

Practical implications

The authors identify some critical issues in the risk-taking processes of MGIs. The tested hypothesis highlights the opportunities for the optimisation of guaranteed loan portfolios, which is necessary for reducing the profitability/liquidity pressures of these financial institutions and enhancing their efficiency as instruments for mitigating the effects of credit rationing and promoting the revitalisation of small-and medium-sized enterprises.

Originality/value

The results are based on an original and reserved dataset, which is not available in public financial statements or public statistics, but is collected directly from the MGIs that are part of the study.

Details

The Journal of Risk Finance, vol. 15 no. 3
Type: Research Article
ISSN: 1526-5943

Keywords

Content available
Article
Publication date: 3 August 2020

Maria Grazia Fallanca, Antonio Fabio Forgione and Edoardo Otranto

This study aims to propose a non-linear model to describe the effect of macroeconomic shocks on delinquency rates of three kinds of bank loans. Indeed, a wealth of…

Abstract

Purpose

This study aims to propose a non-linear model to describe the effect of macroeconomic shocks on delinquency rates of three kinds of bank loans. Indeed, a wealth of literature has recognized significant evidence of the linkage between macro conditions and credit vulnerability, perceiving the importance of the high amount of bad loans for economic stagnation and financial vulnerability.

Design/methodology/approach

Generally, this linkage was represented by linear relationships, but the strong dependence of bank loan default on the economic cycle, subject to changes in regime, could suggest non-linear models as more appropriate. Indeed, macroeconomic variables affect the performance of bank’s portfolio loan, but such a relationship is subject to changes disturbing the stability of parameters along the time. This study is an attempt to model three different kinds of bank loan defaults and to forecast them in the case of the USA, detecting non-linear and asymmetric behaviors by the adoption of a Markov-switching (MS) approach.

Findings

Comparing it with the classical linear model, the authors identify evidence for the presence of regimes and asymmetries, changing in correspondence of the recession periods during the span of 1987–2017.

Research limitations/implications

The data are at a quarterly frequency, and more observations and more extended research periods could ameliorate the MS technique.

Practical implications

The good forecasting performance of this model could be applied by authorities to fine-tune their policies and deal with different types of loans and to diversify strategies during the different economic trends. In addition, bank management can refer to the performance of macroeconomic conditions to predict the performance of their bad loans.

Originality/value

The authors show a clear outperformance of the MS model concerning the linear one.

Details

The Journal of Risk Finance, vol. 21 no. 4
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 22 July 2021

Bernd Engelmann

The purpose of this article is to derive formulas for lifetime expected credit loss of loans that are required for the calculation of loan loss reserves under IFRS 9. This…

Abstract

Purpose

The purpose of this article is to derive formulas for lifetime expected credit loss of loans that are required for the calculation of loan loss reserves under IFRS 9. This is done both for fixed-rate and floating rate loans under different assumptions on LGD modeling, prepayment, and discount rates.

Design/methodology/approach

This study provides exact formulas for lifetime expected credit loss derived analytically together with the mathematical proofs of each expression.

Findings

This articles shows that the formula most commonly applied in the literature for calculating lifetime expected credit loss is inconsistent with measuring expected loss based on expected discounted cash flows. Formulas based on discounted cash flows always lead to more conservative numbers.

Practical implications

For banks reporting under IFRS 9, the implication of this research is a better understanding of the different approaches used for computing lifetime expected loss, how they are connected, and what assumptions are underlying each approach. This may lead to corrections in existing frameworks to make applications of risk management systems more consistent.

Originality/value

While there is a lot of literature explaining IFRS 9 and evaluating its impact, none of the existing research has systematically analyzed the calculation of lifetime expected credit loss for this purpose and how the formula changes under different modeling assumptions. This gap is filled by this study.

Details

The Journal of Risk Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1526-5943

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Article
Publication date: 6 June 2016

Amos Olaolu Adewusi, Tunbosun Biodun Oyedokun and Mustapha Oyewole Bello

This study assesses the classification accuracy of an artificial neural network (ANN) model. It examines the application of loan recovery probability rather than odds of…

Abstract

Purpose

This study assesses the classification accuracy of an artificial neural network (ANN) model. It examines the application of loan recovery probability rather than odds of default as the case with traditional credit evaluation models.

Design/methodology/approach

Data on 2,300 loans granted over the period 2001-2012 was obtained from the databases of Nigerian commercial banks and primary mortgage institutions. A multilayer feed-forward ANN model with back-propagation learning algorithm was developed having classified the sample into training (38 per cent), testing (41 per cent) and validation (21 per cent) sub-samples.

Findings

The model exhibits a high overall percentage classification accuracy of 92.6 per cent. It also achieves relatively low misclassification Type I and Type II errors at 6.5 per cent and 8.2 per cent, respectively. Macroeconomic variables such as gross domestic product, inflation and interest rates have the strongest influence on the ANN model classification power. The result of the analysis shows that adopting odds of recovery in ANN classification models can lead to improved loan evaluation.

Originality/value

The paper is distinct from extant studies in that it presents a new dimension to loan evaluation in Nigerian lending market. To the best knowledge of the authors, the paper is among the first to explore probability of loan recovery as the basis for credit evaluation in the country.

Details

International Journal of Housing Markets and Analysis, vol. 9 no. 2
Type: Research Article
ISSN: 1753-8270

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Article
Publication date: 13 July 2015

Aristeidis Samitas and Stathis Polyzos

The purpose of this paper is to propose an object-oriented model of financial simulations which aims to test the applicability and suitability of the proposed measures of…

Abstract

Purpose

The purpose of this paper is to propose an object-oriented model of financial simulations which aims to test the applicability and suitability of the proposed measures of Basel III with respect to the prevention of banking crises.

Design/methodology/approach

The authors introduce an object-oriented model of financial simulations in the banking sector, namely, virtual banking (VBanking). The system is based on behavioural simulation of economic agents and allows for transactions between them, using various forms of financial assets. VBanking has been implemented as an automated stand-alone model, allowing for repetitive simulations under the same parameter sets, producing an efficient series of statistical data.

Findings

Interpretation of the resulting data suggests that some of the criticism against the proposed measures is justified, as neither economic crises nor contagion are diminished under Basel III. At the same time, the authors’ findings support that the stability goal is met, at least in part.

Research limitations/implications

The model encompasses a relatively small part of the banking sector, while the authors choose not to deal with the production part of the economy. However, these limitations do not hinder the validity and importance of the authors’ findings.

Originality/value

The originality of this article lies in the use of an object-oriented behavioural model and in the resulting model application that is based on it. This enables the authors to run a series of simulations with different parameters, the results of which the authors can then compare. The authors’ findings can contribute to the authorities’ efforts to ameliorate the policies of Basel III.

Details

Journal of Financial Regulation and Compliance, vol. 23 no. 3
Type: Research Article
ISSN: 1358-1988

Keywords

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