Search results

1 – 10 of over 7000
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.

4258

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

Keywords

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 likelihood for…

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

Keywords

Article
Publication date: 15 February 2022

Asish Saha, Debasis Rooj and Reshmi Sengupta

This study aims to investigate the factors that drive housing loan default in India based on unique micro-level data drawn from a public sector bank's credit files with a national…

Abstract

Purpose

This study aims to investigate the factors that drive housing loan default in India based on unique micro-level data drawn from a public sector bank's credit files with a national presence in India. The authors address endogeneity in the loan to value ratio (LTV) while deciphering the drivers of default.

Design/methodology/approach

The study uses a probit regression approach to analyze the relationship between the probability of default and the explanatory variables. The authors introduce two instrumental variables to address the issue of endogeneity. The authors also add state-level demographic and several other control variables, including an indicator variable that captures the recent regulatory change. The authors’ analysis is based on 102,327 housing loans originated by the bank between January 2001 and December 2017.

Findings

The authors find that addressing the endogeneity issue is essential to specify default drivers, especially LTV, correctly. The nature of employment, gender, socio-religious category and age have a distinct bearing on housing loan defaults. Apart from the LTV ratio, the other key determinants of default are the interest rate, frequency of repayment, prepayment options and the loan period. The findings suggest that the population classification of branch location plays a significant role in loan default. The authors find that an increase in per capita income and an increase in the number of employed people in the state, which reflects borrowers' ability to pay by borrowers, reduce the probability of default. The change in the regulatory classification of loan assets by the Reserve Bank of India did not bear the main results.

Research limitations/implications

The non-availability of the house price index in analyzing the default dynamics in the Indian housing finance market for the period covered under the study has constrained our analysis. The applicability of the equity theory of default, strategic default, borrowers' characteristics and personality traits are potential research areas in the Indian housing finance market.

Practical implications

The study's findings are expected to provide valuable inputs to the banks and the housing finance companies to explore and formulate appropriate strategic options in lending to this sector. It has highlighted various vistas of tailor-making housing loan product offerings by the commercial banks to ensure and steady and healthy growth of their loan portfolio. It has also highlighted the regulatory and policy underpinnings to ensure the healthy growth of the Indian housing finance market.

Originality/value

The study provides a fresh perspective on the default drivers in the Indian housing finance market based on micro-level data. In our analysis, the authors find clear evidence of endogeneity in LTV and argue that any attempts to decipher the default drivers of housing loans without addressing the issue of endogeneity may lead to faulty interpretation. Therefore, this study is unique in recognizing endogeneity and has gone deeper in identifying the default drivers in the Indian housing market not addressed by earlier papers on the Indian housing market. The authors also control for the regulatory changes in the Indian housing finance market and include state-level control variables like per capita GDP and the number of workers per thousand to capture the borrowers' ability to pay characteristics.

Details

International Journal of Emerging Markets, vol. 18 no. 10
Type: Research Article
ISSN: 1746-8809

Keywords

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 a…

1978

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. 11 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

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. 13 no. 5
Type: Research Article
ISSN: 1940-5979

Keywords

Article
Publication date: 22 December 2023

Asish Saha, Lim Hock-Eam and Siew Goh Yeok

The authors analyse the determinants of loan defaults in micro, small and medium enterprises (MSME) loans in India from the survival duration perspective to draw inferences that…

Abstract

Purpose

The authors analyse the determinants of loan defaults in micro, small and medium enterprises (MSME) loans in India from the survival duration perspective to draw inferences that have implications for lenders and policymakers.

Design/methodology/approach

The authors use the Kaplan–Meier survivor function and the Cox Proportional Hazard model to analyse 4.29 lakhs MSME loan account data originated by a large bank having a national presence from 1st January 2016 to 31st December 2020.

Findings

The estimated Kaplan–Meier survival function by various categories of loan and socio-demographic characteristics reflects heterogeneity and identifies the trigger points for actions. The authors identify the key identified default drivers. The authors find that the subsidy amount is more effective at the lower level and its effectiveness diminishes significantly beyond an optimum level. The simulated values show that the effects of rising interest rates on survival rates vary across industries and types of loans.

Practical implications

The identified points of inflection in the default dynamics would help banks to initiate actions to prevent loan defaults. The default drivers identified would foster more nuanced lending decisions. The study estimation of the survival rate based on the simulated values of interest rate and subsidy provides insight for policymakers.

Originality/value

This study is the first to investigate default drivers in MSME loans in India using micro-data. The study findings will act as signposts for the planners to guide the direction of the interest rate to be charged by banks in MSME loans, interest subvention and tailoring subsidy levels to foster sustainable growth.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Book part
Publication date: 17 January 2023

Tanseli Savaser, Murat Tiniç, Gunseli Tumer-Alkan and Hakki Deniz Karaman

This study examines whether fintech lending further enhances or mitigates the gender-based differences in consumer loan performance in an emerging market. Using a proprietary…

Abstract

This study examines whether fintech lending further enhances or mitigates the gender-based differences in consumer loan performance in an emerging market. Using a proprietary dataset of over 5.5 million consumer loans offered by the fifth-largest bank in Turkey and its fintech subsidiary, the authors first document a significant gender gap in average loan performances. In line with the previous empirical findings, men are more likely to default on their debt. The average difference in loan performance is around 10 basis points, indicating a statistically and economically significant magnitude even after controlling for an exhaustive list of demographic and credit characteristics. Next, the authors show that the gender gap in loan performance is more pronounced in areas where women have more outside options in terms of social and economic opportunities. Specifically, the authors observe that gender-based differences are predominantly evident in cities with higher divorce rates, lower young and elderly dependence, smaller household sizes, and higher labor force participation of women. Since the child and elderly care duties disproportionately influence women’s ability to participate in economic life, their ability to find resources to pay their loans in a timely manner improves more in comparison to men in areas where women face fewer restrictions to seek local economic opportunities outside the household. Finally, the authors document that fintech loans partially mitigate the gender-based differences in consumer loan performance in those cities. This result suggests that the developments in financial technology can reduce the inefficiencies associated with human involvement in credit decisions, narrowing the gender gap in loan outcomes to the extent that these gaps are attributable to the supply-side factors that involve human judgment and biases.

Details

Fintech, Pandemic, and the Financial System: Challenges and Opportunities
Type: Book
ISBN: 978-1-80262-947-7

Keywords

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 by the…

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

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 systems…

4529

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

Keywords

Open Access
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 literature has…

1492

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

Keywords

1 – 10 of over 7000