• Journal of Information Technology Applications and Management
• /
• v.15 no.3
• /
• pp.43-59
• /
• 2008

This paper studies small and medium sized financial agency's management states that take advantage of the Korea Federation of Saving Bank's data. It also presents the management state and the decision-making model that monitors progressive insolvency by standardizing transfer path between relevant groups. With this in mind, we extracted explanatory variables for predictions of insolvency by using existing studies of document related insolvency. First of all, we designed a state model based on demarcated groups to take advantage of the self organizing map that groups in line with a neural network. Secondly, we developed a transition model by standardizing the transfer path between individual banks in a state model. Finally, we presented a decision-making model that integrated the state model and the transition model. This paper will provide groundwork for methods of insolvency prevention to businesses in order for them to have a smooth management system in the financial agencies.

• Journal of Family Resource Management and Policy Review
• /
• v.23 no.2
• /
• pp.99-115
• /
• 2019

This study examined the insolvency likelihood of young debtors from the 2018 Household Financial and Welfare Survey. This study used the Household Default Risk Index (HDRI), which considers the ratio of total debt to total assets (DTA), and a total debt service ratio (DSR) to examine the insolvency level of debtors. The descriptive analyses showed no difference in frequency of households with a high probability of insolvency between those less than 35 years of age and those over 35 years of age. However, the median HDRI value for those less than 35 years of age was higher than those over 35 years of age. The multivariate analyses indicated that educational expenses for young Korean debtors was a factor that increased their probability of insolvency, while income was the only variable that decreased their insolvency likelihood.

• Journal of Digital Convergence
• /
• v.11 no.1
• /
• pp.13-25
• /
• 2013

After studying FSMA 24, We found that the insolvency rule of financial institutions in FSMA consists of eight provisions: 1) voluntary arrangement, 2) administration order, 3) receiverships, 4) voluntary winding up, 5) winding up by the court, 6) bankruptcy, 7) provisions against debt avoidance, and 8) supplemental provisions in insurance cases. Insolvency provisions in FSMA explain powers and accountabilities of FSA in relation to these insolvency proceedings. Although there are some differences in proceedings, provisions entitle FSA the same status as creditors to petition the court, with a right to participate in related meetings and to be notified of any matters involving insolvency proceedings. The differences and implications between U.K.'s FSMA and Korean regulations are related to the insolvency rule of financial institutions. First, in FSMA, FSA has a comprehensive power to manage insolvency proceedings of financial institutions in a centralized way. However, Korean regulations have special laws to regulate insolvency in a decentralized way. The offices executing those laws are the Financial Services Committee, the Financial Supervisory Service, and the Financial Deposit Insurance Corporation. This characteristic results from an accelerated legislation procedures related to financial reform in 1997 Korean financial crisis. Second, FSA contains special provisions on continuation of contracts of long-term insurance considering the characteristics of insurance industry related to insolvency of financial institution. However, Korean insolvency rules applied to financial institutions do not consider industrial differences and the characteristics of financial contracts, so need to be supplemented in the future.

• Journal of Family Resource Management and Policy Review
• /
• v.22 no.1
• /
• pp.63-78
• /
• 2018

This study examined the insolvency of debtors using multiple-indicator approaches and compared the outcomes across income levels with the 2016 'Household Financial and Welfare Survey'. This study used (1) the total debt to total assets ratio (DTA), (2) the total debt service ratio (DSR), and (3) the Household Default Risk Index (HDRI) recently developed by the Bank of Korea. Households in the lowest income quintile were more likely to be insolvent than any other income group. Demographics, such as age and gender of the household head, and most of the financial variables significantly increased the likelihood of insolvency based on the DTA. The number of household members and job status increased the likelihood of insolvency based on the DSR. Also, age, gender of the household head, and most of the financial variables increased the likelihood of household insolvency based on the HDRI after controlling for other demographics and financial variables.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.319-329
• /
• 2021

The study examines the impact of bank-level factors like non-performing assets, capital adequacy, and insolvency risk on bank performance. This study employs a quantitative method with panel data regression. The data was taken from the annual financial statements of state-owned commercial banks and private commercial banks in Indonesia from 2015 to 2019 using a purposive sampling method with a total sample of 470 observations. The result of the study shows that non-performing assets (NPA) have a significant negative impact on bank performance. Capital adequacy has a significant negative impact on bank performance. Insolvency risk for a bank means it cannot repay its depositors because its liabilities are greater than its assets; therefore, it has a significant impact on bank performance. This study is expected to help banks to understand how to manage the risks they face and to maintain their performance. This study uses 'size' and 'age of bank' as control variables and for credit risk and insolvency risk, Z-Score is used.

• Journal of Navigation and Port Research
• /
• v.48 no.2
• /
• pp.109-115
• /
• 2024

To develop a shipping company insolvency prediction model, we sampled shipping companies that closed between 2005 and 2023. In addition, a closed company and a normal company with similar asset size were selected as a paired sample. For this study, data of a total of 82 companies, including 42 closed companies and 42 general companies, were obtained. These data were randomly divided into a training set (2/3 of data) and a testing set (1/3 of data). Training data were used to develop the model while test data were used to measure the accuracy of the model. In this study, a prediction model for Korean shipping insolvency was developed using financial ratio variables frequently used in previous studies. First, using the LASSO technique, main variables out of 24 independent variables were reduced to 9. Next, we set insolvent companies to 1 and normal companies to 0 and fitted logistic regression, LDA and QDA model. As a result, the accuracy of the prediction model was 82.14% for the QDA model, 78.57% for the logistic regression model, and 75.00% for the LDA model. In addition, variables 'Current ratio', 'Interest expenses to sales', 'Total assets turnover', and 'Operating income to sales' were analyzed as major variables affecting corporate insolvency.

• Proceedings of the Fisheries Business Administration Society of Korea Conference
• /
• 2007.12a
• /
• pp.167-184
• /
• 2007

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut-down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t-test is used to identify the differences in financial variables between the distressed group and the non-distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990$\sim$1993), period 2(1994$\sim$1997), period 3(1998$\sim$2002). The final model built from whole sample appled each three sub-samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub-sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• The Journal of Fisheries Business Administration
• /
• v.39 no.2
• /
• pp.61-79
• /
• 2008

The objectives of this paper are to identify the causes of the corporate distress and to develop a distress prediction model with the financial information in fishery industry. In this study, the corporate distress is defined as economic failure and technical insolvency. Economic failure occurs by reduction, shut - down, or change of the business and technical insolvency results from failure to pay the financial debt of companies. The 33 distressed firms from 1991 to 2003 were composed by 14 economic failure companies, 15 technical insolvency companies. 4 companies applied to the both cases. The analysis of distress prediction of fishery companies were accomplished according to the distress definition. The analysis was carried out as two steps. The first step was the univariate analysis, which was used for checking the prediction power of individual financial variable. The t - test is used to identify the differences in financial variables between the distressed group and the non - distressed group. The second step was to develop distress prediction model with logistic regression. The variables showed the significant difference in univariate analysis were selected as the prediction variables. The financial ratios, used in the logistic regression model, were selected by backward elimination method. To test stability of the distress prediction model, the whole sample was divided as three sub-samples, period 1(1990 - 1993), period 2(1994 - 1997), period 3(1998 - 2002). The final model built from whole sample appled each three sub - samples. The results of the logistic analysis were as follows. the growth, profitability, stability ratios showed the significant effect on the distress. the some different result was found in the sub - sample (economic failure and technical insolvency). The growth and the profitability were important to predict the economic failure. The profitability and the activity were important to predict technical insolvency. It means that profitability is the really important factor to the fishery companies.

• Management & Information Systems Review
• /
• v.34 no.1
• /
• pp.211-225
• /
• 2015

This paper investigate the impact of insolvency cause(internal insolvency cause, external insolvency cause) on firms' turnaround strategies(strategy of improving efficiency, strategy of creating revenue) and examines the impact of firms' turnaround strategies on firms' turnaround performance(debt ratio, sales growth ratio). For this study, a survey was conducted among administrative assistants and four hypotheses were verified. The findings of this research are summarized as follows: First, internal insolvency cause had a positive effect on strategy of Improving efficiency(expense reduction, asset reduction), but external insolvency cause had a positive effect on strategy of creating revenue(product/service reduction, product/service expansion). Second, strategy of improving efficiency positively effect on decreasing debt ratio, but strategy of creating revenue positively effect on the sales growth ratio. These results show that turnaround strategies different across the corporate insolvent cause, and turnaround performance also different across the corporate turnaround strategy.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.5
• /
• pp.3260-3269
• /
• 2014

The construction industry has strong ties with other industries, and so construction company insolvency also has a strong influence on other industries. Prediction models addressing the insolvency of construction company have been well studied. Although factors contributing to insolvency must precede those of predictions of insolvency, studies on these contributing factors are limited. The purpose of this study is to analyze the influence of changes in the housing market on construction company insolvency by using the Vector Error Correction Model. Construction companies were divided into two groups, and the expected default frequency(EDF), which indicates insolvency of each company was measured through the KMV model. The results verified that 10 largest construction companies were in a better financial condition compared to relatively smaller construction companies. As a result of conducting impulse response analysis, the EDF of large companies was found to be more sensitive to housing market change than that of small- and medium-sized construction companies.