• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1591-1598
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• 2014

The reviews of the balance sheet of commercial banks showed that loan item constitutes the largest portion of bank's assets. Although the sector has highest rate of profit, it possesses the greatest risk. Identifying factors that can contribute in lifting-up the loan repayment rate of customers of Hawassa district commercial bank is the major goal of this study. A sample of 183 customers who took loan from October, 2005 to April, 2012 was taken from the bank record. Kaplan-Meier estimation method and univariate Cox proportional hazard model were applied to identify factors affecting bank loan repayment rate. The result from Kaplan-Meier survival estimation revealed that the loan repayment rate is significantly related with loan type, and previous loan experience, educational level and mode of repayment. The log-rank test indicates that the survival probability of loan customers is not statistically different in repaying the loan among groups classified by sex. Moreover, the univariate Cox proportional hazard model result portrayed that educational level, having previous loan experience, mode of repayment, collateral type and purpose of loan are significantly related with loan repayment rate of customers commercial bank. Hence, banks should design loan strategies giving special emphasis on the significant factors while they are giving loans to their customers.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.365-373
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• 2021

Loan monitoring is a fundamental element of credit control. The importance of loan monitoring is to reduce loan defaults and to increase loan repayment performance. The ex-post monitoring can also increase the loan quality and thus a concern to many creditors in the market economy. This study identifies the role of ex-post monitoring on loan repayment performance in the context of rural Vietnam. Employing primary data from rural areas of Vietnam, this study investigates the impacts of ex-post monitoring on loan repayment performance of individual borrowers in terms of on-time loan repayment and the rate of loan repayment. Descriptions of borrower demographics, loan information, and ex-post monitoring show the initial picture of borrowers and loans in Vietnam's rural areas. Quantitative estimations that use the Probit and the Tobit model confirm the argument that better ex-post monitoring would result in better loan repayment performance in both on-time repayment and repayment rate. Thus, some policy suggestions have been made to improve the monitoring system in each financial institution. The study also indicates that some other factors too affect loan repayment performance such as borrower's characteristics (education, agricultural working area, and income) as well as loan's characteristics (loan size, maturity, and loan purpose).

• Journal of Distribution Science
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• v.18 no.5
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• pp.5-13
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• 2020

Purpose: The aim of this article is to test the link between growth of loan distribution and Bank Valuation in Vietnam's banking sector. At the same time, the study also compared the differences in the effect of growth of loan to valuation bank in banks of different sizes, ownership rates and bank values. Research design, data and methodology: With panel data estimation techniques along with robust standard error for a sample of the banks listed on Vietnam stock exchange from 2012 to 2019. Results: Growth of loan has a positive impact on Bank Valuation (by Tobin's Q). A closer investigation provides evidence for the differential valuation effect of loan growth depending on different features of banks. Specifically, loan growth is found positively and significantly associated with Bank Valuation in small and non-state-owned banks only. Besides, bank size, deposit, and return on equity are found negatively associated with Tobin's Q, while loan loss provisions exhibit a positive relation with this measure of Bank Valuation. Conclusions: These findings provide contributions to the literature on the existence of the effect of loan growth on Bank Valuation. At the same time, the study also provides practical implications for policy makers in banks and investors.

• 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.

• Korean Management Science Review
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• v.33 no.3
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• pp.65-87
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• 2016

Being the FinTech technologies rapidly developed, the non face-to-face private loan market is also growing dramatically. While the real-world interests in this market are keen, the empirical studies on the issue are few compared to its prospective impact on credit loan market. This paper suggests a credit scoring model for the non face-to-face private loan employing the ratings approach (the absolute measurement method) of AHP. Analyzing a sample of data consisting of 460,000 transaction records over an 8-year period in the United States, we develop a scoring model for the non face-to-face private loan screening, and validate the model for the practical usage. Conducting sensitivity analysis, we suggest customized cut-off points for the loan execution to suit each individual loan institution's need.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.7-17
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• 2017

Loan consultants assist clients with loan application processing and loan decisions. Their duties may include contacting people to ask if they want a loan, meeting with loan applicants and explaining different loan options. We studied the efficiency of service quality of loan consultants contracted to a bank in Korea. They do not work as a team, but do work independently. Since he/she is not an employee of the bank, the consultant is paid solely in proportion to how much he/she sell loans. In this study, a consultant is considered as a decision making unit (DMU) in the DEA (Data Envelopment Analysis) model. We use a principal component analysis-data envelopment analysis (PCA-DEA) model integrated with Shannon's Entropy to evaluate quality efficiency of the consultants. We adopt a three-stage process to calculate the efficiency of service quality of the consultants. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from survey results in which questionnaire items are constructed on the basis of SERVQUAL model. In the second stage, 3 DEA models allowing negative values are used to calculate the relative efficiency of each DMU. In the third stage, the weight of each result is calculated on the basis of Shannon's Entropy theory, and then we generate a comprehensive efficiency score using it. An example illustrates the proposed process of evaluating the relative quality efficiency of the loan consultants and how to use the efficiency to improve the service quality of the consultants.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.39-48
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• 2015

In this study, granting the optimal loan limit on SME (Small and Medium Enterprise) loans of financial institutions was proposed using the traditional newsvendor model. This study was the first domestic case study that applied the newsvendor model that was mainly used to calculate the optimum order quantity under some uncertain demands to the calculation of the loan limit (debt ceiling) of institutions. The method presented in this study made it possible to calculate the loan limit (debt ceiling) to maximize the revenue of a financial institution using probability functions, applied the newsvendor model setting the order volume of merchandise goods as the loan product order volume of the financial institution, and proposed, through the analysis of empirical data, the availability of additional loan to the borrower and the reduction of the debt ceiling and a management method for the recovery of the borrower who could not generate profit. In addition, the profit based loan money management model presented in this study also demonstrated that it also contributed to some extent to the prediction of the bankruptcy of the borrowing SME (Small and Medium Enterprise), as well as the calculation of the loan limit based on profit, by deriving the result values that the borrowing SME (Small and Medium Enterprise) actually went through bankruptcy at later times once the model had generated a signal of loan recovery for them during the validation of empirical data. accordingly, The method presented in this study suggested a methodology to generated a signal of loan recovery to reduce the losses by the bankruptcy.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.469-490
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• 2018

The purpose of this study is to analyze the status of interlibrary loan (ILL) services using data from its transection. While analyzing the ILL data, agenda to improve the quality of services was identified, and suggestions were made to address them. Three data sets including National Inter-Libary Loan data, National Library Statistics System data, and local inter-library loan system analysis data were collected and analyzed. The results indicate that the size of transaction in ILL is getting bigger. The local ILL, particularly, was expanded and actively used by people. Additionally, the type of library participating in ILL networks was diverse and the number of library was increasing. Finally, this study discussed the tool to measure the contribution of each library in ILL. The collection uniqueness and collaboration index of library as well as the ILL statistics should be considered in the process of the tool development.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.9-18
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• 2019

The purpose of this study is to investigate the relation between conservative loan loss accounting practice of banks, defined as accounting behavior that increases loan loss allowances against expected credit losses, and bank lending. Furthermore, we specify the macroeconomic conditions reflecting debtors' borrowing environments and analyze how these conditions affect the relation between conservative loan loss allowances and bank lending. Although existing literature reports that accounting conservatism has a direct effect on non-financial firms' investment behavior, there is little evidence about an effect of conservatism on banks' lending behavior. By exploiting data showing the links between individual Japanese firms and their individual lenders to control both loan demand and supply, we estimate OLS regressions to test the relationships among conservative loan loss allowance, bank lending, and macroeconomic conditions using a unique dataset containing bank-firm-year observations between 2001 and 2013. We find banks that have conservative loan loss allowances tend to provide fewer loans to firms with financing needs when macroeconomic conditions are good and these conservative banks are likely to provide more loans to firms when macroeconomic conditions are bad. Our findings suggest that reflecting expected credit loss into loan loss allowances can mitigate the procyclical behavior of banks.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1417-1426
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• 2015

We develop the high risk group predictive model for loan default by utilizing the direct loan data from 2012 to 2014 of the Korea Student Aid Foundation. We perform the decision tree analysis using the data mining methodology and use SAS Enterprise Miner 13.2. As a result of this model, subject types were classified into 25 types. This study shows that the major influencing factors for the loan default are household income, national grant, age, overdue record, level of schooling, field of study, monthly repayment. The high risk group predictive model in this study will be the basis for segmented management service for preventing loan default.