• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.83-89
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• 2022

This study analyzed the effect of bank loans on housing prices, classified bank loans into bank total loans, household loans, and real estate mortgage loans, and analyzed housing prices by dividing them into national-level, regional-level, and Seoul-level housing prices. The main analysis results are as follows. First, it was found that the increase in total bank loans significantly increased housing prices across the national-level, regional-level and Seoul-level. Second, it was found that household loans had a positive effect on regional-level housing prices, but were not statistically significant. In addition, the effect of bank loans on regional-level housing prices was found to be relatively small compared to the effect on national-level housing prices. Third, it was found that there was a difference in the effect of bank loans on regional-level housing prices and Seoul-level housing prices. Fourth, inflation and bank total loans had a significant positive effect on regional-level housing prices with a lag in the first quarter, and short-term interest rates had a significant negative effect on Seoul-level housing prices with a lag in the first quarter. Overall, it was found that the effect of bank loans on housing prices had a positive effect about twice that of Seoul-level rather than regional-level.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.1-13
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• 2009

In this paper, we develop theoretical game models to determine the level of government subsidies for banks to provide policy loans to Innovative SMEs(small and medium sized enterprises) through banks, which otherwise would not finance them for the sake of their own profitability. For this, we compare net cash flows of each bank using different strategies against high risk innovative SMEs. A bank can decide whether to provide them loans or not In each period. Following Kim(2003)'s Infinite horizon model on the soft budget constraint, we introduce a situation in which banks compete against each other for higher net long-term payoffs from their loans to innovative SMEs and non-innovative SMEs. From the models, we show that competition among banks in general leads to a tighter decision against innovative SMEs, as a Nash equilibrium. It is not because the government bank is simply loose in providing loans, but because competition among commercial banks for fewer riskier borrowers results in tighter loan decisions against innovative SMEs. Thus, the competitive market for policy loans to innovative SMEs fails to reach the socially optimal level of loans for innovative SMMs. Commercial banks in the competitive market may require additional supports from the government to make up for the differences in their payoffs to support innovative SMEs, possibly much riskier due to moral hazards and poor discounted cash flows. The monopolistic government bank might also request such supports from the government to fund otherwise unqualified SMEs. We calculate an optimal level of governmental support for banks to guarantee funding such high-risk innovative SMEs over periods without deviating from their optimal Nash equilibrium policies.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.647-654
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• 2021

This study examines the non-performing loans of rural banks and macroeconomic factors in Indonesia, including inflation, exchange rates, and interest rates. Theoretically, the existence of erratic macroeconomic conditions can affect the level of non-performing credit risk in rural credit banks in Indonesia. The effect of macroeconomic conditions on non-performing loans has a different response for each economic sector. The main objective of this study is to determine the effect of macroeconomic factors (inflation, exchange rates, and interest rates) and bank-specific factors (credit) on the Non-Performing Loans (NPL) of Rural Banks in Indonesia for the period from January 2015 to December 2018. This study uses a Vector Error Correction Model (VECM) estimation to determine the effect of independent variables consisting of macroeconomic factors and bank-specific factors. Based on the estimation results of the Vector Error Correction Model, three variables that have a positive and significant effect on long-term non-performing loans are credit, inflation, and interest rates. Meanwhile, in the short term, there are only two variables that have a positive and significant effect on non-performing loans, namely, credit and interest rates. Inflation and exchange rate variables have a negative and insignificant effect on bad credit in the short term.

• 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.

• The Journal of Fisheries Business Administration
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• v.47 no.1
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• pp.87-100
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• 2016

Suhyup Bank became to be subject to regulation of capital ratio by Basel III which was introduced in order to enhance stability of the financial institution. Accordingly, Suhyup Bank will require recapitalization. It is important to estimate the risk-weighted assets in calculating of Suhyup Bank's recapitalization scale. Therefor, this study aimed to present a scientific model as estimated the risk-weighted assets. Risk-weighted assets are calculated by applying different risk weights for loans, may have a certain relationship with the loans. Results show that the risk-weighted assets is affected by the previous year's risk-weighted assets and influenced the increase in loans during the year. Since the required basic capital adequacy ratio was specified, the risk-weighted assets should be predicted reasonably. Accordingly, on this study it was tried to derive the accounting equation to predict the risk-weighted assets based on management data of a bank since introduction of Basel III. As the risk-weighted assets were weighted differently according to the type of loans, if the accounting equation is derived by using the type of loans, then it would be helpful for the risk management of banks in the long-term. According to this, the increase of loan would be predicted on the basis of past management performance of Suhyup Bank, and for this reason, the future risk-weighted assets of Suhyup Bank were predicted. The result of this study was showed that 98.3% of risk-weighted assets of the previous year, 62.4% of the secured loan changes and 95.1% of the credit loan changes affected risk-weighted assets.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.19-30
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• 2020

This paper investigates, in a single equation framework, the effect of bank-specific and macroeconomic determinants on micro-, small- and medium-sized loans by commercial banks in Indonesia. This study uses a sample of 790 observations from 79 commercial banks in Indonesia over the years 2006-2015. This study uses two estimation methods for our panel regressions: static and dynamic generalized method of moments (GMM) panel estimator. In static relationships, the literature usually uses the least square methods on fixed effects (FE) or random effects (RE). I found evidence that all banks, bank profitability and size are positively and significantly related to micro-, small- and medium-sized loans, while the coefficients of liquidity are significantly positive in all specifications, except government banks which is significantly negative. The relationship between risk and credit growth is negative for non-government banks. All estimated equations show that the effect of the capital variable on lending banks to MSMEs is not important in government banks and non-government banks. Finally, macroeconomic variables, such as inflation and gross domestic product, clearly affect the lending of the banking sector particularly non-state banks. The findings have several policy implications to Indonesia government, regulatory authority and bank managers in order to improve bank profitability through bank lending.

• Journal of Venture Innovation
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• v.2 no.2
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• pp.117-126
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• 2019

This study conducted correlation analysis and multiple regression analysis using financial statements, loan structure, ROA and ROA volatility of domestic commercial banks, regional banks and special banks for the past five years (2012 ~ 2016). The result is as follows. First, as a result of correlation analysis, bank's ROA is positively related to household loans and SME loans, but it is negatively correlated with the ratio of loans to large companies, sector bias, and loan loss provision ratio. Second, ROA volatility was negatively related to household loans and SME loans, but it was positively correlated with large corporate loans, sector bias ratio, and loan loss provision ratio. Third, as a result of the regression analysis, the variables that have a statistically significant effect on the ROA volatility of banks were household loans, SME loans, and large enterprise loans. From these empirical results, special banks with high volatility in profits need to diversify loan types and sectors in order to achieve business performance outside of policy finance. and Especially, Suhyup Bank and Nonghyup Bank, which have a large commercial role, have a large size per unit by focusing on short-term profit and Rather than focusing on large companies or large loans that are easy to obtain financial information, it is necessary to focus management capabilities on household loans and SME loans by developing capabilities such as screening techniques.

• Asia-Pacific Journal of Business
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• v.11 no.4
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• pp.189-203
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• 2020

Purpose - This study aims in analyzing the dynamic relationship between household loans and housing prices according to the characteristics of depository institutions after the financial crisis, identifying the recent trends between them, and making policy suggestions for stabilizing house prices. Design/methodology/approach - The monthly data used in this study are household loans, household loan interest rates, and housing prices ranging from January 2012 to May 2020, and came from ECOS of the Bank of Korea and Liiv-on of Kookmin Bank. This study used vector auto-regression, generalized impulse response function, and forecast error variance decomposition with the data so as to yield analysis results. Findings - The analysis of this study no more shows that the household loan interest rates in both deposit banks and non-bank deposit institutions had statistically significant effects on housing prices. Also, unlike the previous studies, there was statistically significant bi-directional causality between housing prices and household loans in neither deposit banks nor non-bank deposit institutions. Rather, it was found that there is a unidirectional causality from housing prices to household loans in deposit banks, which is considered that housing prices have one-sided effects on household loans due to the overheated housing market after the financial crisis. Research implications or Originality - As a result, Korea's housing market is closely related to deposit banks, and housing prices are acting as more dominant information variables than interest rates or loans under the long-term low interest rate trend. Therefore, in order to stabilize housing prices, the housing supply must be continuously made so that everyone can enjoy housing services equally. In addition, the expansion and reinforcement of the social security net should be realized systematically so as to stop households from being troubled with the housing price decline.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.923-931
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• 2021

The aim of the present study is to analyze the financial performance of converted commercial bank from non-banking financial institution through a case study of Bangladesh Commerce Bank Limited as sample organization. It is observed that the bank is able to achieve a stable growth rate in total deposits, total loans and advances, and net income after tax during the period of 2015-2019. Researchers also calculated some ratio analysis and noticed that the financial position of Bangladesh Commerce Bank Limited was not so strong because bank's ROA, ROE, NIM and other ratios were below standard. Researchers used secondary data that were examined by using descriptive statistical tools and panel data regression model. Result shows that Bangladesh Commerce Bank has satisfactory operating efficiency, assets management efficiency, and gives loans to customers. In addition, the present study has tested some hypotheses regarding net income after tax, ROA and ROE with total assets, total loans, total deposits and interest income. These hypotheses have been accepted, which means there is no significant influence of the independent variable on the dependent variable. The study suggests that Bangladesh Commerce Bank Limited had the opportunities to make their financial position stronger by utilizing their good financial position and management efficiencies.