The effect of SME reporting framework and credit risk on lenders' judgments and decisions

DeZoort, F. Todd; Wilkins, Anne M.; Justice, Scot E.

doi:10.1016/j.jaccpubpol.2017.05.003

Cited by 9 publications

(9 citation statements)

References 28 publications

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“…The positive effect on interest rate generated by strict bank-firm relationship 3 (longer relationship and a more significant number of accounts) is even more substantial for high-risk SMEs (Neuberger and Räthke-Döppner 2015 ; Peltoniemi 2007 ). In addition to the firm-bank relationship variables, the quality of financial reporting and the non-credit services cross-sold to the company exert a significant effect on the cost of credit (DeZoort et al 2017 ; Peel 2019 ; Santikian 2014 ). Some papers in this cluster (Bartoli et al 2013; Duarte et al 2018 ) also indicate the existence of an unexpected positive relationship between collaterals and bankruptcy for SMEs with high credit-risk levels and the existence of a negative relationship between collateral requirements asked by banks and bank-borrower distance (Bellucci et al 2019 ).…”

Section: Results Of the Vos Analysis And The Systematic Literature Rementioning

confidence: 99%

Rethinking SME default prediction: a systematic literature review and future perspectives

et al. 2021

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Over the last dozen years, the topic of small and medium enterprise (SME) default prediction has developed into a relevant research domain that has grown for important reasons exponentially across multiple disciplines, including finance, management, accounting, and statistics. Motivated by the enormous toll on SMEs caused by the 2007–2009 global financial crisis as well as the recent COVID-19 crisis and the consequent need to develop new SME default predictors, this paper provides a systematic literature review, based on a statistical, bibliometric analysis, of over 100 peer-reviewed articles published on SME default prediction modelling over a 34-year period, 1986 to 2019. We identified, analysed and reviewed five streams of research and suggest a set of future research avenues to help scholars and practitioners address the new challenges and emerging issues in a changing economic environment. The research agenda proposes some new innovative approaches to capture and exploit new data sources using modern analytical techniques, like artificial intelligence, machine learning, and macro-data inputs, with the aim of providing enhanced predictive results.

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Section: Results Of the Vos Analysis And The Systematic Literature Rementioning

confidence: 99%

Rethinking SME default prediction: a systematic literature review and future perspectives

et al. 2021

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“…A number of credit processing considerations may be pivotal in reducing the PLR. The first is existing debt (CDebt), which however, is rarely considered important to Microfinance Institutions (MFIs) and Small and Medium Enterprises (SMEs) who rely on soft information (Abdulsaleh & Worthington, 2016;DeZoort, Wilkins, & Justice, 2017;Lassoued, 2017;Harif, Hoe, & Zali, 2011;Berger, Minnis, & Sutherland, 2017). The second is income, capacity and savings, all of which captures the ability of the borrower to meet the periodic repayment of the interest and principle (Adzobu et al, 2017;Laib, 2013;Abdulsaleh & Worthington, 2016;Koomson et al, 2016).…”

Section: Credit Processing Considerationsmentioning

confidence: 99%

Sector Lending Concentration and Credit Risk: An Evaluation of Lender Perceptions in Tanzania

Alananga

2022

International Journal of Banking and Finance

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This study contributes to the debate on the effect of Lending Concentration (LC) on credit risk. It is based on data from an online survey of 151 employees from 37 lending institutions, employees with diverse experience in the different sections of their institutions. Following a successful three-factor solution on LC based on an Exploratory Factor Analysis, Binary logistic regression models were implemented to determine the Perceived Lending Risk (PLR) based on three types of LC, namely Social Status Lending Concentration (SSLC), Private Sector Lending Concentration (PSLC) and Public Employee Lending Concentration (PELC). It was noted that over- concentration based on social status provided an explanation for the increase in Non-Performing Loans (NPL) risk among both large and small lenders. Since Lending Concentration reverses the effect of macroeconomic variables, such as credit risk management practices (CRMPs), Credit Processing Considerations (CPCs), as well as collateral types, assessing the degree at which the lender is concentrated across sectors is imperative, prior to any credit risk management initiative. Although LC directly affects lending risks perceptions alongside the traditional and corporate finance theories, the indirect LC effect via CRMPs, CPCs, bank size and originality, as well as the various collateral typologies seems to provide new insights into this area of research.

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“…This study examines whether the quality of financial information affects the decisions of finance managers in providing financing to the potential debtors in the context of sharia banks. Some previous researches have addressed the effect of financial statement information on financing decisions in the setting of conventional banks (Berger, Minnis, & Sutherland, 2017;Calcagnini, Cole, Giombini, & Grandicelli, 2018;Cassar, Ittner, & Cavalluzzo, 2015;Chan, Hsieh, Lee, & Yueh, 2015;DeZoort, Wilkins, & Justice, 2017;Donelson, Jennings, & Mcinnis, 2017;Kwok, 2002;. However, few studies have examined the role of financing managers' characteristics in moderating the effect of financial statement information on the financing decisions of shariah banks, especially regional-government-owned Syariah banks.…”

Section: Introductionmentioning

confidence: 99%

Does Financing Decision-Making by Regional Government-Owned Syariah Banks Depend on Financial-Information Quality and Managers' Characteristic?

Putri

Diantimala²,

Saputra³

2021

JRAK

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This study examines the impact of financial information quality on managers’ financing decision-making. It also investigates the role of managers’ characteristics – educational background, gender, and working period – on the relationship between the quality of financial statement information and financing decision-making. The samples were finance managers at Bank Aceh Syariah, a Syariah bank owned by the regional government in Aceh, consisting of 24 finance managers at the branch offices and 86 finance managers at sub-branches that spread throughout Aceh. The data was obtained by using a questionnaire distributed using google form. A multivariate analysis was used to test the hypothesis. The results showed that the quality of financial statement information has a positive effect on financing decisions. It becomes the basis for managers in making financing decisions in Islamic banks owned by local governments. Managers’ characteristics do not influence financing decisions and do not strengthen or weaken managers in making financing decisions based on financial statements. The result confirms hypothesis 1, however, it does not support any other hypotheses regarding finance managers’ characteristics. Therefore, it is suggested for future research to broaden and compare the characteristics of finance managers of national Islamic banks in Indonesia and Islamic banks from other countries to capture comprehensive results.

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The effect of SME reporting framework and credit risk on lenders' judgments and decisions

Cited by 9 publications

References 28 publications

Rethinking SME default prediction: a systematic literature review and future perspectives

Rethinking SME default prediction: a systematic literature review and future perspectives

Sector Lending Concentration and Credit Risk: An Evaluation of Lender Perceptions in Tanzania

Does Financing Decision-Making by Regional Government-Owned Syariah Banks Depend on Financial-Information Quality and Managers' Characteristic?

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