• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.205-212
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• 2020

This study seeks to examine the main factors, external and internal to the bank, that enhance bank lending. Bank lending is one of the connecting bridges in sustaining society. Internal factors consist of ROA, DPK, and CAR. External factors are economic growth and interest rate of Bank Indonesia. The population of this research consists of traditional commercial banks listed on the IDX over the 2014-2017 period. Samples were chosen by purposive sampling method. This study uses secondary data with 56 samples; data analysis uses multiple linear regression. The findings of the study show that internal factors have a greater impact on increasing bank lending than external factors. The main variable among internal factors that influences increase in bank lending is ROA. DPK is the internal factor with the smallest impact on increasing bank lending. The implication of the study is that determining the bank lending should take more account of CAR, DPK, ROA, BI interest rates, and economic growth in making decisions about the amount of lending. These variables can only have a slight effect on increasing lending, though. Besides, internal factors such as NPL, LDR or non-economic factors also need to be considered in channeling bank credit.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.71-78
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• 2019

This study aims to identify good borrowers within the context of P2P lending. P2P lending is a growing platform that allows individuals to lend and borrow money from each other. Inherent in any loans is credit risk of borrowers and needs to be considered before any lending. Specifically in the context of P2P lending, traditional models fall short and thus this study aimed to rectify this as well as explore the problem of class imbalances seen within credit risk data sets. This study implemented an over-sampling technique known as Synthetic Minority Over-sampling Technique (SMOTE). To test our approach, we implemented five benchmarking classifiers such as support vector machines, logistic regression, k-nearest neighbor, random forest, and deep neural network. The data sample used was retrieved from the publicly available LendingClub dataset. The proposed SMOTE revealed significantly improved results in comparison with the benchmarking classifiers. These results should help actors engaged within P2P lending to make better informed decisions when selecting potential borrowers eliminating the higher risks present in P2P lending.

• The Journal of Industrial Distribution & Business
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• v.9 no.9
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• pp.15-23
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• 2018

Purpose - The purpose of this paper is to examine the determinants of non-bank depository institutions (non-bank financial corporations) lending to firms. The paper aims to contribute to the existing literature by providing empirical evidence from firm-level data and unveiling factors related to access to non-bank financial corporations by firms. Research design, data, and methodology - We used the data on borrowing by firms from CRETOP from years 2008 to 2011. Using the manufacturing industry, we examined what firm-level characteristics explained the increase in borrowing from non-bank financial corporations rather than the banks. Results - Analyzing the firm-level data from 2008 to 2011, we found that firms were more likely to borrow from non-bank financial insti­tutions as the size of the firm increases, implying that large firms have more access to non-bank financing than small and medium-sized firms. In addition, it also showed that small and medium-sized firms moved to non-bank financial corporations for loans. Conclusion - Non-bank depository institutions are not a sub­stitute for bank lending to firms. More specifically, they replace bank lending to firms mostly for large firms rather than small and medium-sized firms. Also, collateral and other firm-level characteristics do not matter in accounting for non-bank lending to firms.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.37-46
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• 2018

Purpose - This paper explores the determinants of bank lending to firms during and after the global financial crisis using firm- and bank-level data to answer the questions what caused the contraction of lending to firms despite the loosening monetary policy during this crisis period. Research design, data, and methodology - We investigate the effects of the monetary policy that followed the global financial crisis on firms borrowing. We use a dynamic panel model to address how firms lending respond to monetary policy. The data are obtained from CRETOP and we consider the manufacturing sector for the analysis to control for unobserved heterogeneity such as industry-specific shocks. Results - The findings from the empirical analysis suggest that both bank- and firm-level characteristics are significant determinants of bank lending. Especially, we find that corporate risk, measured by default risk, is one of the key factors that led to a decline in lending during the crisis. Conclusions - This paper shows that companies borrow more from liquid banks, and high bank capital can also contribute to an increase in a firm's borrowing from banks. Especially, the results confirm that the default rate measured at the firm level has increased during and after the global financial crisis, which implies that default risk interplays with other firm and bank-level characteristics.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.697-706
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• 2020

This study investigates the relationship between related loan, ownership concentration and real estate firm performance. The data was collected from 35 real estate firms listed on Indonesia Stock Exchange from 2007 to 2012. Related loans are viewed from the angle of related lending and loan. Related lending and loan is measured by the related lending on total lending ratio and related loan on total loan ratio. Firm performance is measured by the asset turnover ratio and return on assets ratio. Ownership concentration is measured by the right cash flow. The data analysis was done with regression analysis and panel data. The results of the study found that related loans had a positive effect on sales but had no effect on profits. This supports the efficient transaction hypothesis. On the other hand, related lending has a positive effect on profits that supports opportunistic transactions. Ownership concentration moderates the effect of related loan on company's performance. The related lending are beneficial for mutually supporting activities in the real estate sector business group in Indonesia, but related loans have the potential to be used in tunneling activities. The paper contributes to the related party transaction in benefits-risks of related lending and related loan in uncertainty context.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.59-72
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• 2020

This paper examines whether lending structure can lower credit risk by employing econometric techniques of panel data for the Vietnamese banking system at the bank level used by economic sectors from 2011 to 2016. New light is being shed on assessing the impact of each industry's debt outstanding on credit risk. Adopting findings from previous studies, we assess credit risk from two different sources, including loan loss provision and non-performing loan. Moreover, we also focus on observing lending structure in many different aspects, from concentrative levels to the short-term and long-term stability levels of lending structure. The Generalized Method of Moments (GMM) estimator was applied to analyze the relationship between concentration and banking risks. In general, the results show that lending concentration may decrease credit risk. It is interesting to observe that the Vietnamese commercial bank lending portfolios have, on average, higher levels of diversity across different sectors. In particular, the increase in hotel and restaurant lending contributes to decrease credit risk while the lending portfolios of banks in agriculture, electricity, gas and water increase credit risk. This study suggests the need for further analysis and research about portfolio risks in lending activities for maintaining efficiency and stability in the commercial banking system.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.43-51
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• 2022

Platform lending or online lending, sometimes called peer-to-peer (P2P) lending, arose due to the digital revolution to meet people's requirements for simple fund borrowing. It quickly became an alternative to other traditional lending techniques, for example, loans banks. Along with the growth of P2P lending, several academics have investigated how information technology is used in financial services, emphasizing extended application methods. This study proposes an enhanced technology acceptance model (TAM) that investigates how consumers embrace P2P lending platforms by using quality of service and perceived risk as drivers of trust, relative advantage and compatibility as drivers of perceived usefulness. For the purpose of this study, we created a questionnaire, distributed it to clients of P2P lending platforms and fintech services in general in cities in Java, Indonesia. We received 290 replies to our questionnaire. The data was analyzed to test the hypotheses using structural equation modeling (SEM). The findings show that consumers' trust, relative advantage, perceived usefulness, and perceived ease of use in P2P lending platforms substantially affect their views toward adoption. The research's findings are useful for fine-tuning platform marketing strategies and putting strategic goals into action.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.981-992
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• 2021

This study identifies the determinants of potential failure of Islamic Peer-to-Peer (P2P) lending in Indonesia, and the mediating effect of Islamic ethics on reducing the potential for failure of Islamic P2P lending. This study uses primary data retrieved through questionnaires from the perspective of 152 stakeholders in Islamic P2P lending. Using a structural equation model (SEM), the study found that indebtedness, financing size, and governance have positive and significant relationships with the potential failure of Islamic P2P lending. This study provides evidence that the customer's internal conditions and the governance structure applied can increase the potential failure of Islamic P2P lending. Further, Islamic ethics is evidently able to partially reduce the potential failure of Islamic P2P lending by lessening risk management exposure, but it fails to address failure through Ponzi scheme exposure. As an implication, this study suggest that Islamic P2P lending must implement Islamic ethics more comprehensively by optimizing the advisory and supervisory role of the shariah board within their overall boards of directors also in their operational activities. Finally, it also adds to the existing knowledge on financial technology literature, particularly on the determinants of potential failure of financial technology from the perspective of stakeholders.

• Journal of Korean Library and Information Science Society
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• v.50 no.3
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• pp.217-238
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• 2019

Recently, interest in Public Lending Right has increased in Korea. This study aims to collect valuable data necessary for the discussion of the introduction of Public Lending Right by analyzing the loan statistics of 820 public libraries nationwide for five years from 2014 to 2018. In order to analyze the loan statistics of Korean public libraries, 1,178,300,000 big data provided by 'Data for Library' operated by the National Library of Korea were used. Through the analysis of loan statistics, 125 books were identified, which have been lent the most in the last five years. The study examined the 125 books to find out who are authors and Japanese authors and authors' nationality. The study also analyzed publishers and number of lending of cartoons.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3627-3641
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• 2021

Fintech, which stands for financial technology, is growing fast globally since the economic crisis hit the United States in 2008. Fintech companies are striving to secure a competitive advantage over existing financial services by providing efficient financial services utilizing the latest technologies. Fintech companies can be classified into several areas according to their business solutions. Among the Fintech sector, peer-to-peer (P2P) lending companies are leading the domestic Fintech industry. P2P lending is a method of lending funds directly to individuals or businesses without an official financial institution participating as an intermediary in the transaction. The rapid growth of P2P lending companies has now reached a level that threatens secondary financial markets. However, as the growth rate increases, so does the potential risk factor. In addition to government laws to protect and regulate P2P lending, further measures to reduce the risk of P2P lending accidents have yet to keep up with the pace of market growth. Since most P2P lenders do not implement their own credit rating system, they rely on personal credit scores provided by credit rating agencies such as the NICE credit information service in Korea. However, it is hard for P2P lending companies to figure out the intentional loan default of the borrower since most borrowers' credit scores are not excellent. This study analyzed the voices of telephone conversation between the loan consultant and the borrower in order to verify if it is applicable to determine the personal credit score. Experimental results show that the change in pitch frequency and change in voice pitch frequency can be reliably identified, and this difference can be used to predict the loan defaults or use it to determine the underlying default risk. It has also been shown that parameters extracted from sample voice data can be used as a determinant for classifying the level of personal credit ratings.