• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5267-5272
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• 2015

This paper analyzes the relationship between the industry bank loan concentration and its risk using the Korean bank loan data. We focused on the construction and real estate industry which are controversial on the non performing loans. We used the construction or leasing real estate industry bank loan ratio of the corporate bank loan as the bank loan concentration proxies. The bank risk are measured as the equity capital rate or the size of non performing loans. According to the results of this research, the preceding bank loan ration of the construction industry or the leasing real estate industry decreases the non performing loans and increases the equity capital rate. The bank loan concentration to the specific industry may not increase bank risk. The bank loan concentration may decrease the information asymmetry and improve the screening abilities the non performing loans. We suggest that the bank loan concentration on the construction or leasing real estate industry in the Korean economy may not directly connected to the bank risk.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.117-125
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• 2019

This study measured inefficiencies of Korean banks with weighted Russell directional distance function, WRDDM, for the years of 2004-2013. Checking contributions of inputs and outputs to these inefficiencies, we found that non-performing loan as undesirable output was the most influential factor. The annual average of inefficiencies of Korean banks was 0.3912, and it consisted of non-performing loan 0.1883, output factors 0.098 except non-performing loan, input factors 0.098. The annual average inefficiency went sharply up from 0.2995 to 0.4829 mainly due to the sharp increase of inefficiency of non-performing loan from 0.1088 to 0.2678 before and after 2007-2008 Global financial crisis. We empirically showed the non-performing loan needed to be considered since it was the most important factor among the influential factors of technical inefficiency such as manpower, total deposit, securities, and non-performing loan. This study had some limitation since we did not control financial environment factor in WRDDM.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.105-115
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• 2020

The study empirically examines the effects of loan portfolio diversification on bank risk and return in the nascent banking market of Vietnam. Loan portfolio diversification is captured through the Hirschman-Herfindahl index and the Shannon Entropy with sectoral exposures. We access each bank's financial reports to collect the required data, especially the breakdown of sectoral loan portfolios, thus constituting a unique dataset. To compute bank return, we use the traditional accounting indicators, including return-on-assets, return-on-equity, and net-interest margin. For bank risk, we utilize the loan-loss provisions and non-performing loans relative to gross customer loans. Using a sample of 30 commercial banks over the period from 2008 to 2019 and the system generalized method of moments estimator for the dynamic panel, we indicate the downsides of portfolio diversification. Concretely, we observe that all diversification measures exhibit significantly negative signs in all regressions across different bank return proxies. At the same time, the estimates display the significant and positive impact of diversification on the non-performing loan ratio. Hence, sectoral loan portfolio diversification significantly hampers bank performance in both aspects of lower return and higher credit risk. The results are robust across a rich set of bank performance and portfolio diversification measures.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.2
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• pp.35-42
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• 2018

In recent decades, financial crises in various countries have often been preceded by the rise in non-performing loans (NPLs) in the banks' asset portfolios. The increase in NPLs is proven to have adverse impact on the banking sector so that understanding the determinant of NPLs is immensely crucial to ensure the efficiency and soundness of the overall economy. This study aims to shed light on bank-specific factors that affect loan default problems in developing countries whose banking sectors play a major role in the overall economy. This study analyzes panel data sets of 36 commercial banks listed in the Indonesian Stock Exchange during the period 2008-2015. Applying fixed-effects panel regression model reveals that Indonesian banks' profitability and credit growth negatively influence the number of NPLs. Moreover, banks with higher profitability are proven to have lower NPLs because they can afford adequate credit management practices. Likewise, banks with higher credit growth evidently have lower NPLs in the sense that they demonstrate more specialized lending activity and thus have better credit management systems. These findings imply that, in order to lower loan defaults that can deteriorate banks' asset quality, banks should maintain their level of profitability and increase, rather than decrease, their credit supply to debtors.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.9-18
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• 2020

This study seeks to analyze the effect of Non-Performing Loans and Capital Adequacy Ratio on Return on Assets on ten conventional banks listed on the Indonesia Stock Exchange (BEI-IDX). This study uses secondary panel data for 2015-2019 in the form of CAR and NPL values from ten conventional banks listed on the BEI-IDX during the 2020 observation period. The research approach is quantitative descriptive with data analysis methods, namely, linear regression. The testing phase of this study includes: transform value, F-test, T-test and hypothesis test with significancy level sig < 0.05. The results of this study reveal that Non-Performing Loans had a significant negative effect (t = -2,637) (0.011 <0.0) on Return on Assets, while Capital Adequacy Ratio has no significant effect on ROA (0.760 > 0.05). R2 value is 0.128 or 12.8%. It has a significant effect on variables, calling efforts by banks, governments, and authorities monetary of related institutions to maintain the stability of finance. The reduction of Non-Performing Loan impacts on assets and capital adequacy ratio, besides, the normal NPL will control the stability of finance. If a balance is created either in the form of values or amounts of the variables, the reduction in Non-Performing Loans will be controlled.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.591-599
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• 2020

This study examines how the health of the banks in ASEAN-3 countries namely Indonesia, Malaysia and Thailand respond to the change in exchange rates and foreign interest rates in four large economies. The transmissions of the two external factors through domestic factors in each ASEAN-3 countries eventually affects Non-Performing Loan (NPL) of commercial banks. This study uses the monthly time series data and the renowned Structural Vector Autoregressive (VAR) model comprising five variables, namely exchange rate, foreign interest rate, domestic interest rate, money supply, and non-performing loan (NPL). The results indicate that there are different effects between ASEAN-3 countries, which can be classified as short-run effect and long-run effect. In the long run effect, external factors have a dominant role in determining NPL in ASEAN-3 countries. Yuan has the biggest effect on Malaysia's NPL, while Indonesia is more affected by European interest rates rather than the fluctuation of the US currency and China's interest rates. Among ASEAN-3 countries, Malaysia is the one that is the most vulnerable to external factors. While Thailand's NPL is affected dominantly by domestic factors. This study shows that the Fed Funds Rate (US official interest rate) is not always the dominant factor affecting the health of domestic banks in ASEAN-3.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.709-716
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• 2021

The main objective of this research is to find out the effect of Non-Performing Loan (NPL) of Nepalese conventional banks. The population of this study is major commercial banks in Nepal and the data obtained for this study was from the period 2015-2019. This research used secondary data and it is collected from each bank's annual report and GDP and Inflation taken from the World Bank database. The method used for data analysis in this study is multiple regression analysis. The study used NPL as a dependent variable and Return on Asset (ROA), Capital Adequacy Ratio (CAR), Bank Size, GDP growth, and Inflation as independent/explanatory variables. The result of this research shows that ROA, Bank Size, GDP, and Inflation have a significant effect on NPL but CAR does not have a significant effect on the NPL of banks. In other words, the GDP effect on NPL in this study shows a positive and significant effect while most studies show a negative effect. It demonstrates that when GDP growth increases, there is a significant increase in the growth of Nepalese banks even though there were no significant changes in income growth. Therefore, GDP growth has a positive and significant effect on the NPL of commercial banks. Thus, the bankers and policymakers need to consider GDP growth carefully while taking NPL-related decisions.

• The Journal of Fisheries Business Administration
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• v.37 no.3 s.72
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• pp.45-63
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• 2006

A number of public loans with lower interests and other tax benefits have been provided for farmers and fishermen. However, much of those loans have been accumulated as non-performing. The result is that a large part of fisheries debts are now on the verge of default, Those loans, that fail to pay interests, keep rapidly growing like a time bomb. Now something has to be done before it burst. Firstly, the government must clean up the debts caused by government's mismanagement in the past. The past debt must be repaid or written off by the government since its guarantee was committed several times in guidelines regarding public loans. As such a measure, the government can greatly enlarge its capital contribution to the Credit Guarantee Fund for Farmers and Fishermen and Loss Guarantee fund for Policy Loan. It would greatly help to compensate local branches of fisheries cooperatives for their loss incurred from carrying public loans. In the past, the government used to roll over old debts of fishermen with new debts whenever maturity came. It ends up growing the size of non - performing loans. For this reason, it is not delay of the debt payment, but its write - off that fishery society needs a lot. Secondly, the loan authorities must lower overall risk in providing public loans for fishermen in the future. The whole process must be thoroughly reviewed and changed to provide and manage government loans. To facilitate this, fisheries cooperative must stop being just a public agent, rather take a bigger responsibility in selecting, and checking loan beneficiaries, and securing debt repayment. Incentives must be arranged properly enough to induce fisheries cooperatives to treat public loans just like their own business. Finally, the so - called 'special account of policy loan in fisheries industry' must be set up to enhance the transparency and to check the performance of public loans programs.

• The Journal of Fisheries Business Administration
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• v.39 no.1
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• pp.43-61
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• 2008

Excessive public loan with low interest and other tax benefits have been provided for fishermen, but much of them turned out to be little performed. There were the moral hazards of Suhyup in the process of executing the public loans. As the government gave the reimbursement on the financial loss of Suhyup resulting from the public loans, Suhyup had no responsibility of the bad debt loss. Therefore, Suhyup gave little efforts to reduce the non-performing. The government perceived this problem and tried to reduce the under-performing loans. Thus, the government decided to take limited responsibilities. Suhyup made the progress to reduce the under-performing public loans. Suhyup dealt with these situation and made the credit evaluation model of the fisherman's public loan. This paper is for the credit evaluation model in the fisherman's public loan, which explains the model development methodology and the model characteristics in detail. This evaluation model is composed of two sub-component model. the one is the quantitative model and the other is the qualitative model. The quantitative sub-model is for the identification of fishermen financial status and is based on the financial transaction information. Its development methodology is the CSS modeling for the consumer market. The qualitative sub-model is for the evaluation the business prospect and is based on the business information such as fisherman's management skills, technology, equipment. Its development methodology is the AHP. It provides the detailed information in the model development methodology, which is the ideal example such as the public loan. In addition it gives the information to the interest parties such as policy makers, suhyup and fishermen.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.127-135
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• 2020

The paper aims to examine whether business cycles affect the link between financial development and bank risk, measured by Zscore and non-performing loans to total loans in six Southeast Asian countries, namely Indonesia, Philippines, Malaysia, Singapore, Thailand and Vietnam. This study uses a sample of 95 listed commercial banks over a 15-year period between 2004 and 2018 in the six Southeast Asian countries. This study employs panel OLS regression and modifications to tackle issues such as endogeneity and heteroscedasticity. The results show that the impact of stock market development (the ratio of the market capitalization to GDP) on Zscore is significantly positive, whereas its effect on non-performing loans is significantly negative. The findings suggest that financial development, in terms of stock market capitalization, improves banks' Zscores and reduces their level of non-performing loans, suggesting that financial development on average reduces bank risk. The impact of business cycle is insignificant towards bank risk, thus rejecting both counter- and pro-cyclical hypotheses, except for the case of risk indicator of loan loss provisions. Examining the joint effect of the business cycle and financial development on bank risk, we find that the phase of business cycles generally does not moderate the link between financial development and bank risk.