• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.183-192
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• 2020

The purpose of this paper is to investigate the determinants of the Operational Self-Sustainability (OSS) of Vietnamese microfinance institutions (MFIs). This research uses both qualitative and quantitative research methods: (i) qualitative research was via in-depth interviews with ten microfinance practitioners, policymakers and researchers; (ii) quantitative research was conducted by using panel data of 34 MFIs in the period 2011-2015 with binary logistics and OLS regressions. Results are as follows: (i) MFIs' OSS in Vietnam are mainly determined by five key factors: portfolio at risk (PAR>30), capital structure, gross loan portfolio, scope of activities and legal form; (ii) OSS are most affected by legal status (social organizations have better OSS than formal MFIs or programs/projects), location (MFIs focus in one province have higher OSS than working nationwide or just in one district), capital structure (MFIs with more equity proportion have higher OSS); (iii) surprisingly, average loan size per borrower and age of MFIs do not have statistically significant correlation with OSS. The key recommendations are: (i) MFIs should focus on its professionality and increase its equity; (ii) related stakeholders such as State Bank of Vietnam should promote the enabling ecosystem for microfinance development to enhance poverty reduction and economic development.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.129-138
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• 2021

Several studies have revealed that information on borrower characteristics plays an important factor in approving their credit requests. Though the extent to which such characteritics are also applicable to the case of fintech lending remain uncertain. The aim of this study is, thus, to investigate the determinant factors that influence MSEs in obtaining credit through fintech lending. Here, we emphasize virtual trust in fintech lending encompasing the dimension of social network, economic attributes, and risk perception based on several indicators that are used as proxies. Primary data used in the study was gathered from an online survey to the respondents of MSEs in Java. The result of the study indicates that determinants of MSEs in obtaining credit from lender through fintech lending are statistically influenced by internet usage activities, borrowing history, loan utilization, annuity payment system, completeness of credit requirement documents and compatibility of loan size with the business need. These factors have a significant effect on credit approval because they can generate virtual trust of fintech lender to MSEs as potential borrowers. It concludes that the probability of obtaining fintech loans in accordance with their expectations are influenced by the dimensions of social network, economic attributes and risk perception.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.229-238
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• 2019

Before the scholarship loan system was implemented at the Korea Scholarship Foundation, the government's role was strengthened by the direct lending of student funds to banks and other financial institutions. However, the low repayment performance of student loans has raised concerns over the future of student loans and the government's financial burden. Moreover, since student loans are repaid even after graduating from college to support low-income families, it is highly unlikely that the repayment rate of student loans will improve unless the employment rate and income level of the borrower improve. In this paper, the final visualization graph is presented of the repayment amount of the student loan through the collection, storage, processing and analysis phase in the Big Data-based system. This could be the basis for visually checking the amount of student loans to come up with various ways to reduce the burden on the current student loan system.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.177-188
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• 2013

This study examines how managerial ownership structure affects the borrower's choice of private versus public debt using 2,608 firm-year data for 2006-2008. This paper investigates the relationship between managerial ownership structure and debt choice. Managerial ownership is measured using number of stocks and unexercised stock-options and debt is classified public and private debt. The results find that there is a positive association between managerial ownership and the private debt dependence and also find that when firms finance additional funds, higher managerial ownership leads managers to choose private debt not public debt. Since private debt can be classified into bank debt and non bank debt, this paper examines the relationship between managerial ownership and a choice of bank debt. The results indicate that managers with higher ownership are more likely to use bank debt over public debt and non bank debt. By examining the relation between managerial ownership and a debt choice, this paper has following contributions. First, this study shows that managerial ownership affects the choice of the source of financing using three different proxies of managerial ownership. Second, this study classified private debt into bank debt and non-bank debt and provide the evidence of preference toward private debt especially bank debt among other financing sources. Finally, there are extensive studies related to capital structure and managerial ownership, but there is little empirical research on the debt choice and managerial ownership. Thus, this paper adds to literature by exploring the effects of managerial ownership on a debt choice.

• Journal of Arbitration Studies
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• v.19 no.3
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• pp.93-119
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• 2009

Nowadays the number of crimes is increasing rapidly and society is getting more and more dangerous. Recently the criminal aspect of our society, the intelligence, diversity, localized area, as well as for the crime victims also difficult to predict the damage recovery is not easy to change their level of pain and are also serious. This phenomenon is increasingly expected to intensify, the proper response is a factory. The more so if the victim of murder. The criminal mediation working on the operational adjustments Borrower payment, Construction charges, investments and financial transactions due to interpersonal conflicts that occurred as a fraud, embezzlement, breach of trust property crimes such accused, individuals between the defamatory, offensive, encroachment, violating intellectual property rights and private Disputes about the complaint case and other criminal disputes submitted to mediation to resolve it deems relevant to the case who are accused. But the core of a detective control adjustment, adjust the members' representative to the region, including front-line player or a lawyer appointed by the attorney general at this time by becoming parties to this negative view may be ahead. Some scholars are criticizing the current criminal justice system for the absence of proper care for the criminal victims, as an alternative to the traditional criminal justice system. The introduction of the summary trial and related legal cases, the command structure, compensation system, crime victims' structural system can be seen as more classify, crime subject to victim's complaint, By case with a criminal misdemeanor in addition to disagree not punish criminal, minor offense destination, traffic offenders, regular property crime, credit card theft, intellectual property rights violators can be seen due to more categories can try. They sued in law enforcement, Prosecution case has been received and if any one party to the criminal detective Arbitration request arbitration by the parties can agree to immediately contact must be referred to arbitration within 15 days of when the arbitration case will be dismissed. These kinds of early results of the case related to, lawyers are involved directly in the arbitration shall be excluded. Arbitration system is the introduction of criminal justice agencies working to help resolve conflicts caused by adjustment problems will be able to. This article does not argue that we should stick to the traditional justice system as a whole. Instead it argues that the restrictive role of the traditional justice is to be preserved.

• Journal of the Economic Geographical Society of Korea
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• v.13 no.4
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• pp.548-560
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• 2010

This study aims to estimate the payment of farmland reverse mortgage(FRM) and to explore policy considerations about the restructuring of rural area after the initiation of farmland reverse mortgage. Farmland reverse mortgage provides stable monthly income basement for the welfare of rural elderly by liquidating fixed asset such as farmlands which the elderly in rural area owns. The main results of this study can be summarized as follows. First, FRM model based on Housing Equity Conversion Model, which is suggested by Rodda et al (2003), was built. Then, critical factors like farmland value rising rates and interest rates were elaborated, and affordable and proper monthly payment were estimated. 246,982 won, 419,374 won and 757,379 won is given to the borrower at age 65, 75 and 85 respectively with 100,000,000 won value farmland. Second, policy considerations which are necessary for the successful launch of FRM, and restructuring of rural area after launching FRM were discussed. Three policy considerations were proposed. First is about the integrated asset management system for rural elderly people. Second is about the reasonable settlement of corporate farmers system. And third is about the preparations for rural land use planning.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.207-224
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• 2018

In this article, an empirical study was conducted by using public dataset from Lending Club Corporation, the largest online peer-to-peer (P2P) lending in the world. We explore significant predictor variables related to P2P lending default that housing situation, length of employment, average current balance, debt-to-income ratio, loan amount, loan purpose, interest rate, public records, number of finance trades, total credit/credit limit, number of delinquent accounts, number of mortgage accounts, and number of bank card accounts are significant factors to loan funded successful on Lending Club platform. We developed online P2P lending default prediction models using discriminant analysis, logistic regression, neural networks, and decision trees (i.e., CART and C5.0) in order to predict P2P loan default. To verify the feasibility and effectiveness of P2P lending default prediction models, borrower loan data and credit data used in this study. Empirical results indicated that neural networks outperforms other classifiers such as discriminant analysis, logistic regression, CART, and C5.0. Neural networks always outperforms other classifiers in P2P loan default prediction.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.419-437
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• 2023

As the number of thin filers in Korea surpasses 12 million, there is a growing interest in enhancing the accuracy of assessing their credit default risk to generate additional revenue. Specifically, researchers are actively pursuing the development of default prediction models using machine learning and deep learning algorithms, in contrast to traditional statistical default prediction methods, which struggle to capture nonlinearity. Among these efforts, Graph Neural Network (GNN) architecture is noteworthy for predicting default in situations with limited data on thin filers. This is due to their ability to incorporate network information between borrowers alongside conventional credit-related data. However, prior research employing graph neural networks has faced limitations in effectively handling diverse categorical variables present in credit information. In this study, we introduce the Transformer embedded Graph Convolutional Network (TeGCN), which aims to address these limitations and enable effective default prediction for thin filers. TeGCN combines the TabTransformer, capable of extracting contextual information from categorical variables, with the Graph Convolutional Network, which captures network information between borrowers. Our TeGCN model surpasses the baseline model's performance across both the general borrower dataset and the thin filer dataset. Specially, our model performs outstanding results in thin filer default prediction. This study achieves high default prediction accuracy by a model structure tailored to characteristics of credit information containing numerous categorical variables, especially in the context of thin filers with limited data. Our study can contribute to resolving the financial exclusion issues faced by thin filers and facilitate additional revenue within the financial industry.

• Economic Analysis
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• v.25 no.2
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• pp.1-53
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• 2019

This paper examines monetary policy quantitatively in a two-agent and small-scale New-Keynesian economy with debt-constrained households that cannot smooth their consumption intertemporally and frictionlessly since highly indebted households are not allowed to borrow above a certain debt ceiling in incomplete financial markets without additional risk premiums due to information asymmetry between savers and borrowers. We find that, in the event of cost shocks, the asymmetric responses of borrowing households without, and saving households with, dividend incomes lead to different labor supplies and consumptions over heterogeneous households, and eventually to an extension of the monetary policy transmission channels. The income effect and low elasticity of the labor supply play key roles in such asymmetric responses over heterogeneous households. We also find that the social welfare in a flexible inflation targeting (FIT) monetary policy, in which both the inflation gap and the output gap are considered in an integrated manner when policy-making, is similar to that of the Ramsey optimal monetary policy (ROP), in which the shares of debt-constrained households, as well as all economic states, including both the inflation gap and output gap, are considered comprehensively for policy-making, and that it is greater than that of simple inflation targeting (SIT) monetary policy, in which only the inflation gap is considered mechanically for policy-making. Such social welfare implies that a FIT policy may still work even in an economy with a sizable number of debt-constrained households. Further, the responses of cost shocks to consumption and labor supply are dying out more slowly under FIT and ROP policies than under an SIT policy.

• Economic Analysis
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• v.25 no.4
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• pp.1-24
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• 2019

This study examines the labor market performance of graduates who had student loans. Compared to earlier studies, we extended analyses to all jobs that were experienced for more than 18 months after graduation. First, we found that students who had student loans earned 2.81% less at their first job compared to their counterparts without student loans. Second, the wage gap decreased over time, a reduction of 0.66%p due to labor market turnovers. Third, when we compared cumulated labor income, however, the amount for borrowers were continuously higher. This is because the job searching period of a borrower was shorter, despite relatively lower wages at the first job, and borrowers also made more frequent job turnovers, accompanying relatively more wage increases. These results suggest that the negative effects of college loans on earnings, reported in previous studies, may have exaggerated the negative impact to some extent of having loans. However, when we look at the quality of jobs beyond simply wages, the proportion of borrowers working at large companies as regular workers was consistently low. Given that job conditions at the earlier stages of one's career may lead to gaps over time, our findings call for more systematic investigations into the effects that student loans have on long-term labor performance.