• 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).

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.145-158
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• 2017

Lately, rapid increase of household debt and economic change has affected cash flow of household, insolvent risk has increased by high repayment burden of the principal and interest. Previous researches was progressing various discussion, composed objective repayment burden index about household debt. But it was relatively insufficient about perception of consumer. This research compare and analysis determinants of subjective repayment burden in household debt by income quintile, using 2016 Household Financial Welfare Survey. The research result is follows. The income 1 and 2 quartile groups have the higher monthly rent and credit card loan and the housing preparation loan ratio, the higher burden on repayment of the principal and interest. The Income 3 and 4 quartile groups have the higher 60s or older and member of household and real estate mortgage loan, the higher burden on repayment of the principal and interest. The Income 5 quartile group has the higher loan ratio for debt repayment preparation, the higher burden on repayment of the principal and interest.

• 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.

• KDI Journal of Economic Policy
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• v.37 no.3
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• pp.55-74
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• 2015

This study examines the effect of a one-on-one outsourced pre-lending consulting service on the repayment behavior of microcredit borrowers in Korea with administrative data from the Smile Microcredit Bank. A random change in the cut-off loan amount for mandatory consulting is utilized as an identification strategy. This three-day pre-lending business consulting service is effective in encouraging repayment behavior of existing businesses but it has no significant effect on start-up loans. The effectiveness of the consulting service in deterring delinquency with regard to existing loans is greater among male borrowers than among females.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.35-54
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• 2009

The recent economic crisis not only reduces the profit of department stores but also incurs the significance losses caused by the increasing late-payment rate of credit cards. Under this pressure, the scope of credit prediction needs to be broadened from the simple prediction of whether this customer has a good credit or not to the accurate prediction of how much profit can be gained from this customer. This study classifies the delinquent customers of credit card in a Korean department store into homogeneous clusters. Using this information, this study analyzes the repayment patterns for each cluster and develops the credit prediction system to manage the delinquent customers. The model presented by this study uses Kohonen network, which is one of artificial neural networks of data mining technique, to cluster the credit delinquent customers into clusters. Cox proportional hazard model is also used, which is one of survival analysis used in medical statistics, to analyze the repayment patterns of the delinquent customers in each cluster. The presented model estimates the repayment period of delinquent customers for each cluster and introduces the influencing variables on the repayment pattern prediction. Although there are some differences among clusters, the variables about the purchasing frequency in a month and the average number of installment repayment are the most predictive variables for the repayment pattern. The accuracy of the presented system leaches 97.5%.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.85-93
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• 2020

In peer-to-peer (P2P) loan markets, as most lenders are unskilled and inexperienced ordinary individuals, it is important to know the characteristics of borrowers that significantly impact their repayment performance. This study investigates the effects and importance of borrowers' past repayment performance track record within the platform to identify its predictive power. To this end, I analyze the detailed loan repayment data from two leading P2P lending platforms in Korea using a Cox proportional hazard, multiple linear regression, and logit models. Furthermore, the predictive power of the factors proxied by borrowers' track records are evaluated through the receiver operating characteristic (ROC) curves. As a result, it is found that the borrowers' past track record within the platform have the most important impact on the repayment performance of their current loans. In addition, this study also reveals that the borrowers' track record is much more predictive of their repayment performance than any other factor. The findings of this study emphasize that individual lenders must take into account the quality of borrowers' past transaction history when making a funding decision, and that platform operators should actively share the borrowers' past records within the markets with lenders.

• The Journal of the Korea Contents Association
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• v.17 no.6
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• pp.98-105
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• 2017

The medical institution considers liability management problems as a direct factor in managerial risks, such as bankruptcy. Cash Flow provides useful information to necessary funds and predicting bankruptcy. The study for 24 general hospitals and 23 hospitals, a regression analysis was performed to determine the impact of cash flows on the debt repayment capability, a multivariate discrimination analysis was conducted to find out how to manage cash flow for the risk posed by debt. The analysis results, For general hospitals, the level of debt repayment capability was done to net income, increase of payables from operating activities and decrease of patient receivables and inventories from operating activities. If there is no dept repayment capability, it is necessary to increase the net income, increase the expenses not involving cash outflows, decrease of patient receivables and increase of payables from operating activities. For hospitals, the level of debt repayment capability was done to net income, increase of expenses not involving cash outflows and payables from operating activities, decrease of income not involving cash inflows, decrease of patient receivables and inventories from operating activities. If there is no dept repayment capability, it is necessary to increase of payables from operating activities.

• Information Systems Review
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• v.23 no.1
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• pp.69-91
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• 2021

Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

• Journal of Service Research and Studies
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• v.8 no.1
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• pp.103-122
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• 2018

The purpose of this study is to present the direction of ELS investment by analyzing the actual investment return of the ELS commodities and analyzing the investment effect of ELS that investors have felt unsatisfactory at financial marketing service. The research method is based on the step-down type ELS. We calculated the probability of achieving early redemption condition and maturity repayment condition, early redemption estimated yield, and maturity repayment estimated yield. As the study result, the probability of achieving 100% of the early redemption condition was 74.5%, and the probability of the early redemption condition 95% was 83.0%, 90% was 89.5%, 85% was 92.5%, and 80% was 96.5% respectively. In the case of the lowest 75%, the probability of holding to maturity is analyzed to be 2.5%, and the probability of early redemption is high. The probability of the stock price growth within 65% of the maturity repayment condition was 98.5% and the probability of the stock price growth within 60%~45% of the maturity repayment condition was 100%. 65% of maturity repayment condition was analyzed as 1.5% risk of principal loss, and the probability of achieving the committed yield of maturity was high. As a key measure of ELS investment, it is advantageous to select a commodity with a low rate of maturity repayment and a high rate of early redemption.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.537-550
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• 2020

This study attempts to identify gender and age discrimination by individual lenders in P2P lending markets by analyzing empirical transaction data from multiple platforms including Moneyauction, Popfunding, and 8percent. To do this, the study investigates the effects and importance of a borrower's gender and age on individual lenders' preferences and a borrower's actual repayment performance using multiple linear regression and relative weight analyses. As a result, no gender discrimination is found in the three Korean P2P lending markets, and such indiscrimination is rational, on the grounds that the borrower's gender does not have a statistically significant impact on the lenders' preferences as well as his/her actual repayment performance, and its relative importance is minimal. While, there marginally exists age discrimination against a borrower in the markets, and such ageism is likely to be irrational, on the grounds that the borrower's age has a partly significant and minimally important impact on the lenders' preferences, but has no significant and important impact on his/her repayment performance. For the first time, these findings help to clarify gender and age discrimination issues in the P2P lending market by identifying the rationality of individual lenders' preferences to the borrower's gender and age in the Korea.