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Publication date: 12 March 2018

Mohd Yaziz Mohd Isa, Yap Voon Choong, David Yong Gun Fie and Md. Zabid Hj Abdul Rashid

This paper aims to derive determinants of loan loss provisions (LLPs) of commercial banks in Malaysia.

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Abstract

Purpose

This paper aims to derive determinants of loan loss provisions (LLPs) of commercial banks in Malaysia.

Design/methodology/approach

A single-stage panel data analysis multiple regression model that contains a mixture of quantitative and qualitative elements is used. The LLPs is a dependent variable or regressor, and non-performing loan (NPL), interest income, net profit, loans and advances and gross domestic product (GDP) are the independent variables or regressor/explanatory variables. The moderating variable is “credit risk management” (CRM) and the intervening variable is “relevance and faithful representation”.

Findings

This paper suggests in LLPs, NPLs, interest income, loans and advances, net profit and GDP, as well as the moderating effect of CRM and the intervening effect of relevance and faithful representation, are determinants of the LLPs. The moderating variable CRM strengthens the relationship between the independent variables and the dependent variable. The intervening variable “relevance and faithful representation” brings about a more accurate reporting on the levels of the LLPs.

Practical implications

The association of the factors is investigated further to detect possible effect of multicollinearity and research to better understand how banks manage their risk as the current investigation is limited to banks in Malaysia.

Social implications

Loan loss provisioning issues of commercial banks in Malaysia are challenges for both regulators and the banking industry owing to the implementation of several new measures, the convergence with internationally accepted accounting standards and differences in loan grading and applications of different loan loss provisioning standards. Because of these challenges, Bank Negara Malaysia (the Central Bank of Malaysia) has tightened its supervision of commercial banks to ensure that banks are sufficiently and adequately provisioned. The banking sector plays a significant role, and it is important that it is resilient in the face of potential sources of systemic risk. And, like in other major ASEAN economies, the Malaysian’s financial system remains largely bank-dominated.

Originality/value

This study discovers whether Malaysian banks are sufficiently provisioned for the regional financial integration under the ASEAN Capital Markets Forum (ACMF) by the end of 2015, where several initiates have been initiated, including the harmonization of standards to encourage greater intra-regional investment flows and transactions and continued provisions of the much needed funds by the region’s private sectors.

Details

Journal of Financial Reporting and Accounting, vol. 16 no. 1
Type: Research Article
ISSN: 1985-2517

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Article
Publication date: 10 May 2011

Shuk‐Wern Ong, Voon Choong Yap and Roy W.L. Khong

The objective of this paper is to develop a model that can predict financial distress amongst public listed companies in Malaysia using the logistic regression analysis.

5572

Abstract

Purpose

The objective of this paper is to develop a model that can predict financial distress amongst public listed companies in Malaysia using the logistic regression analysis.

Design/methodology/approach

The logistic regression analysis used in this paper is geared towards developing a model that can predict financial distress amongst public listed companies in Malaysia.

Findings

The results prove that five financial ratios have been found to be significant and useful for corporate failure prediction in Malaysia. The overall predictive accuracy is 91.5 percent and this demonstrates that the logistic regression analysis used is a reliable technique for financial distress prediction. In addition, the predictive accuracy of the model in this paper is higher than that of previous studies, which utilised discriminant analysis rather than the method adopted in this research.

Originality/value

The economic crisis mostly began to affect Malaysia's economic standing in July 1997 causing many companies to fall into financial distress, as they were unable to cope with the unexpected downturn. A financial distress prediction model is therefore required to act as a predictor of Malaysian public listed companies' well‐being prior to a financial crisis and to gauge the warning signals of the onset of a downturn in order to strategize their survival techniques during this phase. This study focuses on public listed companies in Malaysia, thus the model adopted is tailored to suit the given context.

Details

Managerial Finance, vol. 37 no. 6
Type: Research Article
ISSN: 0307-4358

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